YugabyteDB_TVA-Datastax.pdf

Total Value Analysis
of YugabyteDB
Anywhere vs.
DataStax Enterprise
Leverage the PRESS framework to evaluate how
your next database can optimize productivity,
resiliency, efficiency, security, and savings.

Total Value Analysis: DataStax
Introduction
Organizations have made significant progress and investment in
transforming their applications and infrastructure over the past decade.
However, one part of the technology stack has remained largely
unchanged: the transactional database.

Most cloud-native applications still rely on traditional monolithic,
relational databases designed before the cloud era. These often take
weeks to provision and are not architected to meet the demands of
modern applications. Scaling to meet growing customer demands
involves manual database sharding, or deploying a cache in front of the
database and dealing with coherence issues. Resilience requires bolt-on
replication solutions.

As organizations expand their global reach, geo-distributing the
database for compliance and performance is a significant, often
expensive, and complex, challenge.

What is the outcome of these legacy database challenges? Expensive
trade-offs, slow innovation, complex operations, and poor customer
experience.

To mitigate the scale and resiliency limitations of traditional relational
database management systems (RDBMS), like Oracle, PostgreSQL, and
DB2, many companies turned to NoSQL solutions like Apache Cassandra
and variants such as DataStax Enterprise. These database solutions
made it simple to achieve cloud scale and resiliency. However,
organizations had to give up the familiarity and power of SQL and strong
consistency, often a high requirement for business-critical transactional
applications.

While Cassandra and DataStax Enterprise offer an acceptable solution
for many use cases, over the past ten years, a new wave of database
innovations emerged in the form of distributed SQL databases. These
modern, re-architected databases combine the core capabilities of both
SQL and NoSQL into a single, powerful database. One that can help
modernize existing applications and match the needs of cloud-native
applications.

In this paper, we compare DataStax Enterprise, a popular enterprise
NoSQL database built on Apache Cassandra, and YugabyteDB
Anywhere, the simplest way to deploy and manage YugabyteDB at scale
for large enterprises.

To compare these two solutions, we used the PRESS framework which
evaluates how organizations can improve across five areas: productivity,
resilience, efficiency, security, and savings.

The objective of this paper is to help you compare YugabyteDB Anywhere and DataStax
Enterprise across a number of key areas. We have created a reference guide that considers the
short and long-term impact of both databases. This enables you to make an informed decision
that aligns with your organization's business requirements.

The paper is structured around the five critical parameters that make up the YugabyteDB PRESS
framework:
Executive Summary
The definition of the five parameters:
Productivity: Increase your rate of innovation and differentiation by bringing new ideas to
production faster.

Resiliency: Ensure apps work seamlessly without any major impact on performance, even
when experiencing node, zone, region, or cloud failures.

Efficiency: Enable database operators to offer an internal DBaaS, make high-impact changes
frequently, and manage more apps with fewer resources.

Security: Secure data anywhere, patch security issues in a timely manner, and limit threat
surface by easily rotating security credentials.

Savings: Reduce both upfront and ongoing costs by optimally allocating or reclaiming
resources as needed.
Productivity Resiliency Efficiency
Security Savings

We have assigned ratings to (YugabyteDB delivered as a self-managed
database-as-a-service) and DataStax Enterprise for each of the criteria above. This takes into
account the ease of each solution meeting the requirements, and the features currently
available. Although we have done thorough research into the third-party offerings, you should
use this paper as a guide and also conduct your own analysis.

Below is a brief summary. A more detailed analysis of our findings follows later in the paper.
YugabyteDB Anywhere
PRESS
Framework
YugabyteDB
Anywhere
YugabyteDB
Anywhere Ranking
Reason
DataStax Enterprise
Ranking Reason
DataStax

Enterprise
Resiliency
Architectural
resilience, geo-
distribution, zero
downtime, RPO = 0s,
RTO = 3s, automatic
sharding, HA/DR
Challenges with  
geo-distribution,
demanding backup
and restore
5 out of 5 4 out of 5
Efficiency
Faster deployments,
operational
efficiency while
scaling, automatic
large partition
splitting, enhanced
compaction
management
Operationally challenging
expansion and upgrades,
challenges with
background compaction,
issues with garbage
collection, bottlenecks
while scaling, large
partition issues, time
consuming read repairs
Savings
License cost savings,

high data density,
infrastructure cost
savings, third party
tools savings,
database
consolidation savings,

labor efficient
operations,

improved
organizational
profitability
Low data density per
node, extreme hardware
and hardware refresh
costs, high operator to
developer ratio, cost of
eventual consistency,
high storage costs,

high scaling costs, high
replacement server costs
Security
End-to-end built-in
security, growing set
of key certifications,

expanded KMS
options, periodic
credential rotation,

zero downtime
patching,
maintenance, and
upgrades
Mature set of
certifications, adherence
to GDPR compliance,

support for key
management services
Productivity
Faster time to value,
accelerated
migration, easy day
2 ops, strongly
consistent
secondary indexes
Complex data modeling,
Indexing and querying
challenges, manual
secondary index tables,
challenges with
OpsCenter

A need for the power and flexibility of SQL Queries: These organizations
want to be able to add new queries quickly and efficiently, as well as
respond to new and changing business needs without requiring new data
models or additional copies of their data. YugabyteDB offers a flexible,
multi-API upper half with the industry’s best PostgreSQL compatibility (the
YSQL API) and a Cassandra-inspired API, YCQL
A need for consistency (ACID), scale, and resiliency: Many companies
sacrificed data consistency for scale and resiliency, but now realize they
can simplify the lives of their operations and app development teams as well
as fix data inaccuracy issues with YugabyteDB.
A need for rapid horizontal scalability: YugabyteDB enables the rapid
addition of new nodes to respond quickly to traffic spikes or new business
needs. While it can scale, DataStax is very hard and slow to scale once in
production, because bootstrapping new nodes requires rebalancing. Users often
have to size their growth into the initial footprint, so they must bear the cost of
overallocated resources that may be wasted or remain unused for a while.
A need to lower hardware and maintenance costs: YugabyteDB provides
much higher density per node, 5 - 10+ TBs per node as well as a
significantly lower overhead for garbage collection. As a result,
organizations that want to dramatically reduce their upfront and ongoing
hardware costs should strongly consider YugabyteDB. Existing YugabyteDB
enterprise customers have seen their cluster sizes reduced by 10x
compared to DataStax and Cassandra.
A need for secondary index support: Organizations face, or will face,
performance issues with Cassandra’s limited support of secondary indexes.
They are looking for a solution (like YugabyteDB) that offers the core
features of NoSQL along with more of the core relational database
capabilities, such as secondary indexes.
YugabyteDB is a leading distributed SQL database designed for organizations
running business-critical, transactional applications. YugabyteDB Anywhere
simplifies delivering a self-managed database-as-a-service (DBaaS) at scale,
whether deployed on-premise or in a public or hybrid cloud.

YugabyteDB Anywhere is the ideal fit for organizations that require strong
data consistency and the familiarity of popular APIs (both PostgreSQL and
Cassandra) along with key cloud native features like high availability,

geo-distribution, and horizontal scalability.

Organizations that are a better fit for YugabyteDB than DataStax Enterprise
will have one or more of the following requirements.
When should y
ou consider
adopting YugabyteDB Anywhere?

When should y
ou consider DataStax Enterprise?
We recognize that some applications may not yet need the capabilities that come with
YugabyteDB’s modern architecture. DataStax Enterprise (DSE) is a high-performance, scalable,
and globally distributed database solution built to handle a high volume of data. It has wide
adoption, a strong community, and a range of available resources and tools, making it easy to
find support and solutions.

Organizations often have a portfolio of databases used by different business units and
applications, based on specific needs and the skill sets available. For non-transactional
applications or smaller applications where data consistency, as well as hardware and storage
efficiencies, are not a high priority, DataStax Enterprise works well.

Cassandra-based databases, like DataStax Enterprise, deliver value and are well-suited for
applications that share one or more of the following characteristics:
If none of these are current or potential pain points for your organization, and you have the
existing staff on hand that understands (or is already operating) a Cassandra environment,
modernizing to a distributed SQL database like YugabyteDB may not be a high priority at this
time. However, you should keep these considerations in mind, so you can recognize them early
if your applications continue to scale and data accuracy becomes more important.
Overall, DataStax Enterprise may be a good choice for businesses that prioritize availability and
only need to handle moderate amounts of data where there are minimal concerns about large
infrastructure sprawl and associated costs. DataStax Enterprise may not be the best fit for
businesses that require strong consistency, multi-API support, or low operational complexity.
Consistency is a low priority (i.e., not a priority system of record workload): DataStax
Enterprise offers eventual consistency with scale and resilience that is sufficient for many
workloads, but does not offer ACID level consistency.
Asynchronous replication for more than three regions: Organizations can consider DataStax
Enterprise when they need specific replication configurations such as hub/spoke models and
N: N bi-directional replication
Flexible eventually consistent options: YugabyteDB is a distributed relational database that
delivers ACID level consistency for distributed transactions. Cassandra provides a range of
weaker consistency options, providing tradeoffs on performance and how they achieve
eventual consistency (but today, that’s never ACID-level consistency).

Weencourageyoutodoyourownresearchintothetechnical
featuresandbusinessvaluethateachsolutionoffers.Youcan
finddetailedYugabyteDBdocumentationonlineat
docs.yugabyte.com.
DataStaxEnterprise is an on-premises database offering from
DataStax. It is a distributed cloud database built on the open-source
NoSQL database Apache Cassandra. DataStax Enterprise provides
high scalability, availability, and performance for modern applications
that require real-time data. DataStax Enterprise includes features
such as multi-datacenter replication, automatic management of data
distribution and replication, search capabilities, and graph
processing. It also includes a visual management tool called DataStax
OpsCenter, which provides a dashboard for monitoring and managing
the entire database cluster.

DataStax Enterprise has been around for over a decade, which
means it has a strong community and there is a wide range of
resources and tools. As a result, organizations can find support and
locate required skills fairly easily.

YugabyteDBAnywhere is the self-managed database-as-a-service
offering of YugabyteDB, the cloud-native distributed SQL database
of choice for business-critical transactional applications. YugabyteDB
is 100% open source and uniquely combines enterprise-grade
relational database capabilities (including distributed ACID
transactions) with cloud native operational simplicity, resilience, and
the ability to scale as you go. YugabyteDB offers a multi-API
interface, allowing developers to leverage either a PostgreSQL or
Cassandra-inspired API. YugabyteDB can be deployed anywhere and
is cloud and platform agnostic.

YugabyteDB Anywhere delivers a management and orchestration
layer on top of YugabyteDB to simplify deployment and management
at scale. YugabyteDB Anywhere automates provisioning, unifies  
real-time monitoring, simplifies security management, manages cloud
infrastructure, and offers a multi-cloud API—all backed by 24x7x365
support. YugabyteDB Anywhere helps customers accelerate time to
market, achieve operational efficiency, and unlock developer
productivity. Yugabyte University enables organizations to connect
to a global community of business leaders, architects, developers
and database practitioners and advance your YugabyteDB learning
journey through interactive learning and knowledge sharing for free.
OverviewofProducts

Here, we will examine how YugabyteDB Anywhere and DataStax Enterprise (DSE) compare using
the five elements of the PRESS framework (Productivity, Resilience, Efficiency, Security, and
Savings). By measuring against these five key considerations, you can ensure you choose the
best database for your business and IT priorities.
Using PRESS to Choose the Right Database
PRODUCTIVITY
An organization's ability to deliver rapid innovation and stay ahead of the competition is often a
direct result of how efficient its developers are. Do developers have the time and tools required
to deliver new services or revenue-impacting enhancements? Or, are they required to spend
valuable time building workarounds into the application to handle various gaps and tradeoffs in
their existing database solutions?

Along with these common issues, database migration challenges can be a major barrier. It can
slow down, or in many cases prevent, cloud-native and application modernization projects from
moving forward. Organizations can significantly boost their rate of innovation and
competitiveness by focusing on new solutions that minimize these challenges and decrease
time to value.

Both YugabyteDB Anywhere and DataStax Enterprise offer an alternative to Apache Cassandra.
DataStax Enterprise simply extends Apache Cassandra while YugabyteDB Anywhere offers a
modern distributed storage layer with a powerful Cassandra-compatible API on top.

These are very different approaches, which impact overall productivity differently. Based on our
analysis, YugabyteDB’s modern architecture gives it an advantage, avoiding many common
productivity issues that exist with Cassandra and Cassandra-based solutions like DataStax
Enterprise.
YugabyteDB: DSE:

YugabyteDB Productivity Advantages
YugabyteDB Anywhere is designed to power highly available, scalable, and strongly
consistent transactional applications, while making database and operation teams
more productive with advanced automation for large-scale deployments. By reusing
core PostgreSQL code for the front end, developers can use existing skills and tools.

Compared to DataStax Enterprise, YugabyteDB helps developers:
Support diverse skills and tools: YugabyteDB provides a flexible query layer with
two key APIs: Cassandra (YCQL) and PostgreSQL (YSQL). Developers familiar with
either PostgreSQL or Cassandra can build on their existing skills and tools to write
to a familiar API while taking advantage of a modern, distributed storage layer.
This flexibility enables developers to get started quickly and minimizes their
learning curve.
Add powerful queries as needed: The PostgreSQL-compatible API of
YugabyteDB allows for simple relational SQL transactions and queries. As new
business needs arise that require a new query, they can be implemented quickly
and easily without needing changes to the data model or new copies of the data.
Enjoy strongly consistent data: YugabyteDB delivers strongly consistent, ACID
transactions across a distributed, scalable database. As a result, developers do
not need to handle common consistency issues like read after write, concurrency
controls, and more, within the application.
Manage large-scale deployment: YugabyteDB Anywhere helps you move away
from manual, complex Day 2 operations, especially for large clusters. YugabyteDB
Anywhere intelligently orchestrates your database scaling, upgrades, backups,
monitoring, and security operations across your public, private or hybrid
infrastructure. This helps optimize your systems for performance
Leverage the power of global secondary indexes and JSONB: Using advanced
indexes can enhance database performance by enabling the database server to
find rows faster. YugabyteDB supports strongly consistent (ACID) secondary
indexes to help you quickly retrieve data using columns that are not part of the
primary key. YugabyteDB supports global secondary indexes, partial indexes, and
covering indexes in addition to JSON and JSONB for added data type flexibility
and productivity in both YSQL and YCQL.
Migrate quickly: helps you migrate from the most common
legacy and single-cloud relational databases to YugabyteDB quickly and easily.
This newly launched migration engine can manage the entire lifecycle of database
migration, including cluster preparation for data import, schema migration, and
data migration.
YugabyteDB Voyager
Interns at
Finserv
Company Learn
YugabyteDB 
in Days
YugabyteDB's strong
PostgreSQL compatibility
allowed interns new to
YugabyteDB to deliver
powerful projects to
Fiserv. An executive at
Fiserv shared a story
about working with a set
of college interns. Fiserv
gave them a problem to
solve--something they
planned to build into a
product--and told them
to use YugabyteDB. The
interns knew

PostgreSQL but had
never touched
YugabyteDB before. After
a couple of days of
Google searches and
some testing, they were
off and running,
capitalizing on their
existing PostgreSQL
knowledge and
experience, and applying
this to YugabyteDB
without any problems.

DataStax Enterprise Challenges
DataStax Enterprise has a number of features that
can assist with productivity, including real-time
data processing, high scalability, support for
multiple data models, and mature monitoring and
management. Compared to the restrictions of
legacy databases, DataStax Enterprise aims to
help organizations streamline their operations,
increase efficiency, and optimize their workflows.

However, there are several challenges that users
report can negatively impact their organizational
productivity:
Expensive data modeling: When migrating to
DataStax Enterprise, customers need to invest
more in redesigning their data model as this is
critical to system stability (including indexes,
partitions, etc.). Users need to carefully consider
data access patterns and partition keys to
ensure that their data is distributed and queried
efficiently before deploying. Also, modifying a
data model once deployed is pretty
cumbersome. In addition, it’s also tough to get
data out of DataStax Enterprise if you don’t
model it properly and you may require additional
third-party tools like Solr or Spark integration to
make it work.
Indexing and querying challenges: Like
Cassandra, DataStax Enterprise provides high
performance when reading or writing data from a
data model specifically designed for the
operation. However, adding a query to help with
a new business need or question is complex and
time-consuming. The lack of support for joins
and subqueries can make it difficult to perform
certain types of data analysis. DataStax
Enterprise also has indexing and querying
limitations, such as the non-availability of mixed
indexes, a requirement of manual triggering
when adding nodes before indexes are built for
the first time, and architectural changes needed
due to index limitations like the mixed index.
Manual secondary index tables: Support for
secondary indexes is much less effective than in
YugabyteDB, as secondary indexes are stored locally
and require reads from every node in the cluster. As
DataStax Enterprise documentation notes,
“secondary indexes are tricky to use and can impact
performance greatly.” DataStax Enterprise requires
secondary index tables to be explicitly handled by
the Application layer
Hard to manage at scale: The DataStax Enterprise
OpsCenter has challenges when monitoring larger
clusters and requires manual effort and support
intervention. OpsCenter was primarily designed to be
a dashboard for monitoring and cluster lifecycle
management, and was bolted on later hence the
cluster management challenges. This greatly brings
down operational productivity.
DataStax Enterprise

Users Identifies Challenge
of Data Modeling
Data modeling is very painful and
prevents us from having a model that
matches most of our use cases. We
have some tables as an index to help on
that issue. We tried Solr, but for a real-
time workload, it does not fit. The
configuration of a Solr index is still too
complex (too many settings and tricks),
it should be possible to declare it with a
single instruction. We use Spark on
Cassandra nodes (with the building
option). At the beginning, it was the
easy choice, but now we think that it
could be a mistake to mix application
workload and Spark workload with the
same servers. Datastax recommends
using a dedicated DC for Spark, but that
comes with an extra cost for new
servers and data stay licenses.
“
(Source: Gartner Peer Insight, VP Engineering, 2023)

RESILIENCY
We live in a world where customers require instant access to information and data. Businesses
are expected to deliver 24x7x365 services that are always available to customers, wherever
and whenever they are in the world. The data behind those apps has become the lifeblood of
these modern organizations.

However, cloud failures and outages are becoming normal. Over the past 18 months, we’ve seen
a major cloud outage occur, on average, every 50 days. As we continue to see regular major
cloud failures, just “moving to the cloud” is not a good enough strategy for high availability.
Organizations need to evaluate the backbone of their data, their database, to ensure they can
meet customers’ demands with minimal performance impact if something goes down.

NoSQL saw major growth 10+ years ago because it delivered a distributed architecture that
provided native resiliency and security—something not easily accomplished with traditional,
monolithic relational databases. With distributed SQL databases, like YugabyteDB, that is no
longer true. Organizations can now get relational capabilities with the resilience and availability
needed for today’s cloud-native, transactional applications.

Both YugabyteDB and DataStax Enterprise are known for providing a distributed, highly-
available database that can survive a wide variety of failures. If availability is your primary
requirement, then both systems can address that need. However, the newer architecture of
YugabyteDB provides additional advantages that might be important to your organization when
evaluating overall resiliency and availability.
YugabyteDB Resiliency Advantages
As a distributed database, YugabyteDB’s core architecture ensures fault tolerance, partition
tolerance, continuous availability, and disaster recovery. These resiliency benefits position
YugabyteDB as a great choice for organizations requiring the capabilities of a relational
database with the resilience and availability of NoSQL.

As you examine which database solution works best for your use cases, YugabyteDB’s
architecture provides some key differences compared to DataStax Enterprise. These features
can help you stay resilient by enabling you to:

Ensure consistent data for geo-distributed users: YugabyteDB is inherently geo-distributed
and allows organizations to access data locally with confidence. Users do not need to worry
about losing transactions or reading stale data, which can happen in the eventually consistent
model of NoSQL. YugabyteDB prioritizes data consistency, so even during failures, any data
read will be the most current. This is a key requirement for true System of Record applications.
YugabyteDB: DSE:

Major Retailer
Shrugs Off

4-Day Azure
Outage with
YugabyteDB
A global retail leader that
runs its product catalog
on YugabyteDB powered
through a major winter
storm that brought down
an entire Azure region for
over four days. Thanks to
multi-region replication,
the retailer only faced a
few seconds of delay
when the other region
took over, and they had
zero data loss and no
impact on their
customers. Data and
traffic were automatically
rebalanced to the other
region in just three
seconds. Meanwhile,
their legacy databases
were offline for days,
with their team working
around the clock for days
to correct the issue and
bring everything back
online.
Deliver consistent backups and restores: YugabyteDB supports fully consistent
backups and restores, scheduled incremental backups, and point-in-time
recovery to the millisecond. Data backups can be taken numerous times daily
without impacting performance, allowing recovery from even the most serious
crashes in minutes, even for critical transactional applications
Rolling upgrades with zero downtime: Yugabyte sets high standards for data
retention and performance when the cloud provider whose service YugabyteDB
is running on suffers a zone outage. YugabyteDB is designed to deliver a
Recovery Point Objective (RPO) of 0 (meaning no data loss will occur during
failures) and a Recovery Time Objective (RTO) of ~3 seconds. i.e. to recover and
resume operations from the new zone. YugabyteDB also performs rolling
maintenance, patching, and upgrades on multi-node clusters with zero
downtime.
Simplified App Development: Resiliency and consistency are powered by the
distributed data layer, meaning developers do not need to worry about resolving
availability and consistency issues in the app. As a result, app development is
easier but also ensures that data and applications are protected completely
without risking human error or issues at the application layer.
DataStax Enterprise provides a masterless architecture for zero downtime to help
meet strict enterprise availability requirements. Organizations can maintain
uninterrupted services even during unexpected outages or disasters, ensuring that
they can continue to operate and meet the needs of their customers. Within the
CAP theorem, Cassandra prioritizes availability, ensuring nodes will always
respond to requests, even if it means the data is not accurate.

However, there are some challenges to be aware of that might negatively impact
your application resiliency and user experience:
Stale reads or data loss: The high availability in DataStax Enterprise relies on
replication to ensure data availability. However, the replication can introduce
data consistency issues if not properly managed. If there is a delay in
replication, a read operation on a replica node may return stale data or lose
data if a failure happens before new data can be replicated
Demanding backup and restore operations: The local backup (snapshot)
process in DataStax Enterprise demands a non-trivial amount of disk space.
DataStax currently does not support hot backup capabilities and needs to
improve the ease of backup. OpsCenter provides a fairly simple restore
process up to a certain scale, but if you have too many backups, it can run into
challenges restoring the data.

EFFICIENCY
From born-in-the-cloud FinTech, Retail, and Telco companies, to large, entrenched leaders,
businesses across all industries face increased competition. To be successful, organizations are
searching for ways to increase profitability by reducing legacy costs and shifting valuable
resources to growth initiatives.

Flexibility and operational efficiency are critical to this process, with many organizations
offloading day-to-day management tasks in favor of as-a-service offerings. Organizations are
also investing in strategic initiatives to finally abandon legacy, “status quo” IT solutions (and
their high costs) in search of modern and often open-source solutions. At the same time, there
is a heightened focus on helping developers to focus on high-impact initiatives.

YugabyteDB and DataStax Enterprise, both have several advantages over monolithic databases
like Oracle and DB2. However, DataStax Enterprise is still limited by many of the core challenges
and limitations of Apache Cassandra. Built by some of the original Facebook architects that built
Cassandra, YugabyteDB introduces a new architecture, one that builds on the lessons of
Cassandra and addresses many of its gaps, especially around overall efficiency.

When comparing the two databases, YugabyteDB stands out as delivering significant
advantages across a few key areas of efficiency, including scaling complexity, hardware costs,
and resource efficiency.
YugabyteDB Efficiency Advantages
Applications can achieve efficiency with YugabyteDB by leveraging its high-performance
capabilities, scalability, consistency, and multi-cloud support. With YugabyteDB, applications
can process more transactions in less time, handle large volumes of data, reduce costs, and
ensure that data is secure, and compliant with regulatory requirements.

YugabyteDB helps you drive database and application efficiencies with:
Fast scalability and node additions: YugabyteDB can scale applications within hours, even in
large clusters. The same operation can sometimes take days for large clusters and
applications deployed on Cassandra-based environments. A new node can be bootstrapped
quickly by copying already compressed data files from the leader of the corresponding shard,
versus the complex and time-consuming process of Cassandra. Clusters can also be easily
expanded with new or bigger nodes without requiring downtime
Reduction in manual tasks: The underlying distributed storage layer of YugabyteDB
eliminates many manual tasks common with Cassandra and other legacy databases.
YugabyteDB automatically splits large partitions, saving days of manual effort for a DBA.
YugabyteDB: DSE:

GM Sees 10x
Improvement in
App Processing
Time
GM runs one of its most
critical connected
vehicle applications on
YugabyteDB where they
process 3 million
messages a second and
improved app processing
time by 10x. The Vehicle
Data Factory (VDF)
application ingests data
from over 20M
connected vehicles,
which means they need a
truly high performant
database. GM previously
ran the application on
Cassandra, which
provided great
availability but failed to
deliver the scalability and
performance needed for
a fast-growing
application. The team
performed extensive
testing on YugabyteDB,
pushing it to the edge
and stretching the
performance. In the end,
they were able to deploy
YugabyteDB into
production within their
desired timeframe and
are positioned to support
their future wave of
vehicles, which continue
to generate more data
and a higher frequency.
Resource efficient transactions: In Apache Cassandra, basic read-modify-write
operations (also known as compare-and-set) use a scheme known as lightweight
transactions, which incurs a four-round-trip cost between replicas. With
YugabyteDB, these operations only involve one round trip between the quorum
members
Enhanced compaction management: YugabyteDB breaks down compactions
into major and minor compactions and schedules them in different queues and
with different priorities. This guarantees a certain quality of service to the
smaller, critical compactions, keeping the impact of background compactions on
the user application to a minimum
Efficient self-service and automation capabilities: YugabyteDB Anywhere
capabilities like self-service deployments & Day 2 automation capabilities,
including rolling upgrades, data backup/restore built-in monitoring, and
automated health checks, all contribute to these efficiencies.
For smaller environments or focused use cases, many of the mature and proven
capabilities of DataStax Enterprise are a good fit, especially when the efficiency
impact on resource utilization, hardware costs, and operational efficiencies are
less important. However, many organizations have seen their applications explode
in size and usage over the years, and are now focusing more on overall efficiency
and exploring other options.

For these companies, there are some key efficiencies challenges with DataStax
Enterprise that they want to eliminate, including the following:
Repeated duplication of data: One of the common approaches within a
Cassandra-based environment is to make a new copy of the data to avoid
changes or impact on the first copy. For multi-region environments, DataStax
Enterprise replicates the data completely in each region with multiple copies per
region. If you have a replication factor of three, then three copies of the data will
exist in each region—consuming lots of resources and impacting overall
efficiency. If you want to introduce a new query, then usually the table is copied,
a new data model is applied, and you have to manage another replica.
High compaction overhead: On average, YugabyteDB only requires about 20%
overhead to handle compactions. DataStax Enterprise requires over double that,
with 50% being the standard overhead recommended. In addition, as node
density increases on DataStax Enterprise, performance is impacted more during
garbage collection and compaction tasks. A major source of slowdown in
DataStax Enterprise is background compactions. As organizations try to increase
space efficiency, they face more and more performance issues.

Slow scaling and upgrades: Expansions and
upgrades are operationally challenging in
DataStax Enterprise and can take several hours
to days, depending on the volume of data stored.
Scalable applications with a high data growth
rate will warrant frequent cluster expansions and
add significant operational overhead to a
DataStax Enterprise environment. Adding a node
in DataStax Enterprise requires a logical read
(i.e., a quorum read) across multiple surviving
peers to bootstrap a new node. All of these
reads must uncompress and recompress the
data. Users report having to keep change control
windows open for days while waiting for a new
node to be added, balanced, and ready to go.
High Read Latency: Within a DataStax Enterprise
environment, anti-entropy, read-repairs, and
additional operations regularly hurt performance.
Read operations need to read from quorum to
limit issues with data consistency. As a result, a
replication factor of three means you may have a
third of the throughput.
Slow garbage collection: In Java-based NoSQL,
long garbage collection (GC) pause is a  
well-known issue.
DataStax Enterprise Discuss  
Performance and Operational Challenges
There can be inconsistency with read/write performance, especially when maintenance operations
occur. We get far more timeouts than expected from the platform, and though the software
handles the case, our performance metrics and SLA gets impacted accordingly.
(Gartner Peer Insight, Chief Architect)
“
We underestimated the operational overhead of setting up and managing a DSE cluster. There are
a number of 3rd parties that offer cloud and on-premise managed services for DSE, and in
hindsight, we should have utilized these services far earlier.
(Gartner Peer Insight, Technical Architect)
“

SECURITY
Companies need to build a trusted data environment with robust data security and privacy while
also governing data policies for ongoing compliance. To achieve this, it is essential that
customers choose databases that have uncompromising security, with core security features
built in from the start making it easy and seamless to enable. Customers look to harden security,
achieve compliance, and mitigate risks before moving their applications and data to the cloud.

YugabyteDB and DataStax Enterprise both recognize the importance of security. Both have a
strong security focus that spans product development to certifications and ongoing security
testing. DataStax Enterprise delivers a number of security enhancements on top of Apache
Cassandra, while YugabyteDB has taken advantage of building a secure, distributed storage
layer to help deliver advanced capabilities.

Despite DataStax Enterprise being in the market for longer, we feel both solutions are focused
on security. There are some differences in what they deliver, so you’ll need to decide if certain
security aspects are more important to you than others. Because of the close ratings for both of
these, below we highlight some of the key features for each and recommend you do further
research and determine which aligns to your priorities best.
YugabyteDB Security Features
Security was a key design principle for YugabyteDB, and the database offers an end-to-end
encryption, RBAC, authentication, authorization, audit logging, SSL/TLS, network security, and
more. These features help ensure that data is protected from unauthorized access, reducing the
risk of data breaches and other security threats. Applications that require high levels of security,
such as healthcare and financial applications, can benefit greatly from YugabyteDB's security
features.
Certifications: ISO 27001, SOC 2 Type 2, SOC 3, and GDP
End-to-end security focus: YugabyteDB leverages a holistic approach to security. The
product design approach is consistent with the SD3+C (Secure by Design, Secure by Default,
Secure in Deployment and Communication) development methodology and spans all
deployment options for YugabyteDB: YugabyteDB (OSS), YugabyteDB Anywhere, and
YugabyteDB Managed.
Native geo-partitioning: Modern policy controls limit user privileges and pin data to specific
regions, which is a requirement for meeting certain regulations like GDPR
KMS choice: YugabyteDB supports an expanded choice of Key Management Services (KMS)
for developers that include Google and Azure in addition to HashiCorp Vault and AWS KMS.
YugabyteDB: DSE:

Narvar Meets
Compliance
Requirements
with

Geo-Distribution
Narvar, a trusted provider
of personalized services
to over 800 retailers
around the world, faced
the ever-changing
requirements from
various countries on data
security and compliance.
With YugabyteDB, they
leveraged the native
geo-partitioning
capabilities to easily
meet various
requirements. The native
geo-partitioning
capabilities made it easy
to keep their retail
customers' user data
pinned to a specific
region or country.
Periodic credential rotation: Credentials are rotated every few months, not
every year (or more), making your applications highly secure
Granular security: Row and column-level security. Note: row-level security is
available for YSQL but not currently available for YCQL (Cassandra-compatible
API).
Zero downtime maintenance: YugabyteDB performs rolling maintenance,
patching, and upgrades on multi-node clusters with zero downtime. Patches to
fix common vulnerabilities and exposure (CVE) take no time to deploy. Operating
system software version upgrades and database software upgrades can be
carried out without downtime.
DataStax Enterprise Security Features
Applications can achieve security with DataStax Enterprise's database
management software by leveraging its encryption, RBAC, audit logging,
authentication, authorization, and compliance features. These features help ensure
that data is protected from unauthorized access, reducing the risk of data
breaches and other security threats.
Certifications: DataStax supports a set of compliance, regulations, and
certifications including PCI, SOC 2 Type 2, HIPAA, and GDPR
Adherence to GDPR compliance: DataStax aligns GDPR compliance with
hybrid cloud needs
Support for Key Management Service: DataStax supports third-party KMS
support and BYOK (Bring Your Own Keys)
Granular security: Row and column-level security. DSE adds row-level access
control (RLAC), which is unavailable in normal Apache Cassandra.
Geo-partitioning: Can be achieved using DataStax Enterprise Graph (DSE
Graph) database.

SAVINGS
While the technical capabilities of a database and the business outcomes they can drive are
often analyzed first when researching a new database, in today’s economic environment, it’s
important to quickly analyze overall costs and prioritize solutions that can lead to meaningful
savings.

To successfully increase profitability, organizations need to find ways to lower costs, such as
reducing expensive legacy database licenses or removing less efficient solutions. Ultimately,
you should prioritize solutions that help you shift finite budgets for hardware, software, and
people to higher-impact, value-added initiatives. This means moving away from legacy
databases that have been in use for 10+ years, as newer solutions, like distributed SQL
databases, provide a number of cost savings—in terms of the license and required hardware
costs—and overall efficiency savings.

Here, we completed an in-depth analysis of the costs of both YugabyteDB and DataStax
Enterprise using a sample scenario that closely aligns with a real-world customer workload we
recently helped support. As a result of significant hardware savings and lower overall license
costs, YugabyteDB resulted in over 2x savings in licensing and infrastructure costs alone. Below
is a summary of the highlights of the savings that companies can achieve with YugabyteDB. You
can also review a more detailed analysis in Appendix A.
YugabyteDB Savings Advantages
Organizations can achieve cost savings with YugabyteDB by leveraging its lower license costs
(free for the OSS version), high data density, built-in automation, and easy management
features. These features help companies avoid the high costs of proprietary software, expensive
hardware, downtime, and manual database management.

In the detailed cost comparison outlined in Appendix A, the following areas were the primary
reason that YugabyteDB achieved over 2x savings compared to DataStax Enterprise:
License cost savings: Software licensing costs for YugabyteDB Anywhere are far less than
legacy databases, with a list price over 80% less than DataStax Enterprise. As well as lower
pricing, YugabyteDB includes all core database features without additional fees. In fact, all core
database features are available for free in the open-source (OSS) version of YugabyteDB. The
licensed version of YugabyteDB Anywhere provides advanced management and automation
capabilities, along with 24x7 support, to assist with enterprise deployments at scale.
YugabyteDB: DSE:

High data density: YugabyteDB supports higher data density per node while still
delivering the necessary performance with high throughput and low latency.
DataStax Enterprise can handle around one to two TB per node (and sometimes
less), while YugabyteDB supports five to 10 (or more) TB per node for. most use
cases. This means that YugabyteDB's data density greatly reduces your
hardware footprint, lowering upfront hardware costs and lower operating costs
over time.
Infrastructure cost savings: The infrastructure costs of YugabyteDB versus
DataStax Enterprise are far less, coming in at over 60% less in our example
outlined in Appendix A. YugabyteDB helps drastically reduce these costs thanks
to much higher data density per server. Cost savings are also realized during
hardware refresh cycles. Customers can use inexpensive commodity hardware
without the need for specialized vendor hardware, an in-customer data-center,
or the public cloud using any form factor (VMs, Containers/K8s, Bare-Metal)
Consolidation savings: YugabyteDB supports a diverse set of workloads thanks
to its multi-API support, with PostgreSQL and Cassandra-compatible APIs. Users
have the opportunity to reduce database sprawl, consolidate their apps on fewer
databases, and greatly reduce operational complexity.
Labor efficient operations: The automation and simplicity in YugabyteDB
Anywhere help to reduce the ratio of operations personnel to developers.
Customers are able to achieve ratios in the order of 1 operator to 100 developers.
Improved organizational profitability: With high availability and resiliency
features built into YugabyteDB, revenue loss due to downtime can be eliminated.
As a result, organizations can preserve their top-line revenue, so the bottom line
(profit) stays high
SaaS Retail
Partner
Reduces TCO
by 4x with
YugabyteDB
Narvar was one of many
organizations that saw
their cloud costs rise to
unexpected levels due to
the highly variable and
throughput-based
pricing of their public
cloud database. They
had used the Amazon
DynamoDB database
earlier but due to rising
costs as a result of their
business growth,
especially around the
peak retail seasons, they
had to rethink their
database modernization
strategy. Narvar made
the decision to switch to
YugabyteDB and as a
result, achieved 4x lower
TCO, gaining scale and
performance, all while
avoiding cloud lock-in.

High infrastructure costs: The low data density
of DataStax Enterprise, usually at most 1 - 2 TB
per node, results in a cluster size that can be 5x
or larger than that required for supporting the
same size workload with YugabyteDB.
High hardware refresh costs: Given the larger
cluster size needed for DataStax Enterprise,
costs to refresh and update the cluster are
significant. Scaling times are also higher, resulting
in high refresh operating costs.
High Operator-to-Developer ratio: The operator-
to-developer ratio for DataStax Enterprise can be
over 2x that of YugabyteDB.
Cost of eventual consistency: The eventual
consistency of DataStax Enterprise means there
is a possibility of inconsistent data in any replica.
To address this, DataStax Enterprise uses Read
Repair and Anti-entropy maintenance processes
- expensive and resource-intensive operations
that slow down apps.
High Storage costs: Usable storage per node in
Cassandra is about 50% because of compaction
overheads, further driving up storage costs
High License Costs: The DataStax Enterprise list
price is over 5x higher than YugabyteDB
Anywhere.
DataStax Savings Challenges
DataStax Enterprise delivers a number of key enhancements and features to Apache Cassandra, however,
those additional features come at a cost. In addition, some of the issues that result in higher costs for
Cassandra deployments, like low data density, mean DSE users can face higher costs due to the need for larger
clusters and more storage.

Companies can achieve cost savings with DataStax Enterprise by leveraging its scalabidata center-native
architecture, lack of vendor lock-in, high availability, operational efficiency, and advanced analytics features.
However, some challenges with DataStax Enterprise increase costs for companies, including:

Conclusion
YugabyteDB Anywhere and DataStax Enterprise both deliver additional features and automation
on top of open-source databases (YugabyteDB and Apache Cassandra). By comparing these
two offerings using the PRESS framework, we’ve focused on how the modern, distributed SQL
database architecture of YugabyteDB provides a number of advantages when it comes to
productivity, resiliency, efficiency, security, and savings. Some of the well-known challenges
with Cassandra result in similar challenges for DataStax Enterprise users.

Our Total Cost of Ownership analysis showed that a DataStax Enterprise environment is 2.2
times more expensive than YugabyteDB Anywhere for the same workload under consideration.
Cost savings are a direct result of lower license costs and huge savings in hardware costs, both
upfront and ongoing maintenance, thanks to the much higher data density per node possible
with YugabyteDB.

For organizations considering DataStax Enterprise, we have found that in most cases
YugabyteDB Anywhere can actually offer a better Cassandra experience with strong
consistency and better TCO than achievable with DataStax Enterprise due to the challenges it
inherits from its Apache Cassandra foundation.

Our PRESS analysis provides key areas for you to consider when evaluating your next database
modernization initiative. In addition to the points we have addressed, it’s also important that you
research the additional capabilities and benefits a distributed SQL database, like YugabyteDB, can
provide, in addition to the specific advantages over DataStax Enterprise we’ve covered here.

We invite you to learn more about and also consider whether a self-managed
DBaas offering like , aligns more closely with your needs. You can get
started by signing up for a (or) to learn more.
YugabyteDB
YugabyteDB Anywhere
free trial request a demo

Below are additional details for comparing the TCO of YugabyteDB
Anywhere to DataStax Enterprise. Every application will have
slightly different requirements, so use the below model as a
general guide that can be adjusted based on your specific needs.

For the real-world scenario modeled below, a YugabyteDB
Anywhere environment provides a 2.3x better TCO compared to
DataStax Enterprise.

Appendix A:

Detailed TCO Analysis
Section I: Assumptions and Modeled Scenario
To compare the TCO of YugabyteDB Anywhere and DataStax
Enterprise, we chose a specific scenario that closely models that
of a real-world customer comparing the two database solutions.
For the TCO analysis, we modeled a multi-region, synchronous
deployment with the following assumptions for our calculation:
Total database size = 20 T
Deployment spans across 3 regions for  
high availability and disaster recover
Replication Factor (RF) = 3
Number of tables = 3
Number of indexes =
Number of reads/unit = 30,000 reads per second
Number writes/unit - 10,000 writes per secon
Average size of read = 32 K
Average size of write = 4 K
The per-hour labor cost of a DBA employed full-time is
assumed to be 51.75 USD per hour
Infrastructure costs

For the infrastructure cost calculations, we use M5.4x large AWS
EC2 instances for both YugabyteDB Anywhere and DataStax
Enterprise. We assume constant availability and usage of
dedicated M5.4x instances that are 16 cores/node and 64+ GB
Memory/node with 15 Gigabit network performance on Linux OSes.
The instances are reserved for a period of 1 year and 3 years,
respectively, for the 1-year and 3-year TCO calculations, with all
payments upfront to AWS to optimize for costs.

Section II: Required Configuration
YugabyteDB Anywhere Configuration

For the architecture under consideration with a 20 TB database, YugabyteDB Anywhere
(YBA) is configured to be spread across 3 clusters. Based on the model scenario we are
using, the nodes for YBA need a total of 144 cores and 576 GB of memory. YBA has a low
compaction overhead of 20%, and we’ll assume an optimal data density of 8TB per node. We
have allocated 1 DB Admin FTE for managing the DB infrastructure and DB operations.
DataStax Enterprise Configuration

For the architecture under consideration with a 20 TB database, the DataStax Enterprise (DSE)
deployment spans across two clusters in two data centers. The nodes need 640 cores and
2,560 GB of memory. DSE has a high compaction overhead of 100% and a low data density. For
this calculation, we use 3TB per node. We have allocated 2 DB Admin FTE for managing the DB
infrastructure and DB operations, as there are significantly more nodes, disk storage,
infrastructure, and hardware refreshes to manage compared to YugabyteDB Anywhere.
YBA nodes calculation

Number of YBA nodes = ((Raw Data * ( 1 + Compaction overhead%)* RF)/Data Density)/
Clusters)*Clusters

Number of YBA nodes = ((((20* (1+ 20%)*3)/8)/3)*3)

Number of YBA nodes = 9 nodes
YBA total disk space calculation

YBA Total disk needed = (Raw Data (1+ Compaction overhead) RF)*No of Datacenters

YBA Total disk needed = (20(1+20%)*3)*1

YBA Total disk needed = 72 TB of disk space
DSE nodes calculation

Number of DSE nodes = ((Raw Data * ( 1 + Compaction overhead%)* RF)/Data Density)/
Clusters)*Clusters

Number of DSE nodes = ((((20*(1+100%)*3)/3)/2)*2

Number of DSE nodes = 40 DSE nodes
DSE total disk space calculation

DSE Total disk needed = (Raw Data (1+ Compaction overhead) RF)* Number of Datacenters

DSE Total disk needed = (20 (1+100%)*3)*2

DSE Total disk needed = 240 TB of disk space

Section III: License Costs
The license cost data for YugabyteDB Anywhere, and DataStax Enterprise includes software
license costs per core/node for 1-year or 3-years. Non-production license costs are included in
all options, providing a basis for comparing the direct license costs of both databases.
Section IV: Infrastructure costs
The infrastructure cost data includes a breakdown of direct costs for both YugabyteDB
Anywhere and DataStax Enterprise over 1 year and 3 years. Costs include compute costs,
DBA costs, storage, snapshot space, backup storage costs, AWS data transfer costs, and
KMS costs.

The total infrastructure costs provide a basis for comparing the overall infrastructure costs of
both databases based on the workload and infrastructure requirements under consideration.

License Costs (DIRECT)
Total License Cost per year

Non-prod license costs
$ 259,200.00

Included
$ 777
,600.00

Included
$ 380,000.00

Included
$ 1,140,000.00

Included
$ 259,200.00 $ 777
,600.00 $ 380,000.00 $ 1,140,000.00
Total License Costs (Direct)
YBA - 1 Year YBA - 3 Years DSE - 1 Year DSE - 3 Year
Infrastructure Costs
(DIRECT)
Compute - Cloud VM total
upfront costs (Reservation
instances (upfront costs))

Compute - Normalized
reserved instances (Total
cost over 1 or 3 years)

Compute - Cloud VM total
costs (EC2 M5.4X large)
$ 39,240.00

$ 52,560.00

$ 91,800.00
$ 79,200.00

$ 157
,680.00

$ 236,880.00
5.00

730.00
$ 174,400.00

$ 52,560.00

$ 226,960.00
$ 352,000.00

$ 157
,680.00

$ 509,680.00
DBA costs for maintaining
the infrastructure
$ 99,360.00 $ 298,080.00 $ 198,720.00 $ 596,160.00
SSD volumes gp3  
(Rounded to whole instances)

Average duration 
each instance runs  
(Hours per month)
5.00

730.00
15.00

730.00
15.00

730.00

20 20 20 20
KMS - no of unique keys
Infrastructure Costs  
(DIRECT)
Provisioning iOPS per volume

Snapshot frequency (Daily)

General Purpose SSD (gp3) -
Throughput

Amount changed per snapshot
(TB)
16,000.00

4x

1000 MB/s per
volume

1.00
16,000.00

4x

1000 MB/s per
volume

1.00
16,000.00

4x

1000 MB/s per
volume

1.00
16,000.00

4x

1000 MB/s per
volume

1.00
EBS Storage Cost

EBS IOPS Cost

EBS gp3 Throughput cost

EBS Snapshot Cost
$ 6,553.60

$ 325.00

$ 175.00

$ 19,541.76
$ 6,553.60

$ 325.00

$ 175.00

$ 19,541.76
$ 19,660.80

$ 975.00

$ 525.00

$ 58,625.28
$ 19,660.80

$ 975.00

$ 525.00

$ 58,625.28
General purpose SSD Storage -
EBS monthly cost

General purpose SSD Storage -
EBS Annual cost

Backup storage - S3 Standard -
monthly

Backup storage - S3 Standard -
annual

Total Storage costs 
( Storage + Backup)
AWS Data Transfer - Inbound
data transfer (TB/month) (10 TB
is good / same for OS C and YBA)

AWS Data Transfer - Intra-region
data transfer (TB/month)

AWS Data Transfer - Outbound
data transfer (TB/month)

Network data transfer (Regional
data transfer) - AWS Data  
transfer - monthly costs

Network data transfer  
(Regional data transfer) - AWS
Data transfer - annual costs
$ 26,595.36

$ 319,144.32

$ 1,673.22

$ 20,078.64

$ 339,222.96
20 TB

20 TB

20 TB

$ 1,024.00 

$ 12,288.00
20 TB

20 TB

20 TB

$ 1,024.00 

$ 36,864.00
20 TB

20 TB

20 TB

$ 1,024.00 

$ 12,288.00
20 TB

20 TB

20 TB

$ 1,024.00 

$ 36,864.00
$ 26,595.36

$ 957,432.96

$ 1,673.22

$ 60,235.92

$ 1,017,668.88
$ 79,786.08

$ 957,432.96

$ 5,457
.92

$ 65,495.04

$ 1,022,928.00
$ 79,786.08

$ 2,872,298.88

$ 5,457
.92

$ 196,485.12

$ 3,068,784.00

License Costs (DIRECT)
KMS - no of symmetric  
requests

KMS - Total Monthly cost

KMS - Total Annual cost
$ 26.00

$ 312.00
$ 26.00

$ 312.00
$ 26.00

$ 312.00
$ 26.00

$ 312.00
$ 542,982.96 $ 1,589,804.88 $ 1,461,208.00 $ 4,211,800.00
Total Infrastructure costs

(Direct)
$ 802,182.96 $ 2,367,404.88 $ 1,841,208.00 $ 5,351,800.00
Total Costs
2000000 2000000 2000000 2000000
About Yugabyte,Inc.
Yugabyte was founded in 2016 by former Facebook and Oracle engineers with decades of
experience building business-critical database systems and operating them in production. 
The company was named a 2020 Cool Vendor by Gartner and is backed by Sapphire Ventures,
Lightspeed Venture Partners, Dell Technologies Capital, 8VC, Wipro Ventures, and others.
Get In Touch

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