Couchbase is a document-oriented NoSQL database that provides a distributed key-value store with optional in-memory caching. It uses JSON documents with a schema-free approach and has built-in replication and high availability. Couchbase supports low-latency applications through its in-memory operations and integration with memcached. It allows flexible scaling through horizontal sharding of data across nodes.

1. Desc Score WS
Database type 2%
Key-Value, document database,
JSON, schemaless, high
availability in-
memory(Caching)
asynchronous persistence and
cache model formed as a merger
of Apache Couch DB and
memcache. Does provide a
mobile DB synced with original
DB-no other DB has it. Has
inmemory solution which Mongo
and Accumulo do not have.
99 1.98
Best used 2%
Any application where low-
latency data access, high
concurrency support and high
availability is a requirement. Can
be used as OLTP for inmemory
transactions.
99 1.98
Use Cases and
Adaptability(specific
to ADP)
2%
Low-latency use-cases like ad
targeting or highly-concurrent
web apps like online gaming (e.g.
Zynga).
66 1.32
Storage Type 2%
Key-Value with inmemory
document datastore
99 1.98
General Key Facts -
10%
Metrics Sub Metric
Weighted
Score
CouchBase

2. Characteristics 2%
very flexible but rather slow
indexes
66 1.32
Data Storage 2% Volatile memory, File System 99 1.98
Unicode 1% Yes 99 1.98
Search Integration 2% External Plug-in 66 1.32
Compression 1% Yes 99 1.98
Conditional Entry
updates
1% Yes 99 1.98
TTL for Entries 1% Yes 99 1.98
Graph support 2% No 0 0
Rich Design &
Features - 10%

3. Query Language 2%
JavaScript, Memcached-protocol
Gartner's survey reports
difficulties integrating with
other DBMS.
33 0.66
Programming
language
2%
C, C++, Erlang. More language
support is needed.
33 0.66
Ease of use(JSON) 2% Yes 66 1.32
Protocol Used 2% memcached + extensions 66 1.32
MapReduce 2% Yes 66 1.32
Integrity model 2% MVCC. No SPOF 99 1.98
R & D Velocity
Acceleration - 10%
Integrity - 10%

4. ACID transactions 5%
Couchbase claims to be ACID-
compliant on a per-item basis,
but has no multi-operation
transactions. Couchbase clients
connect to a server list (or via a
proxy) where keys are sharded
across the nodes. Couchbase
nodes inherit memcached’s
default (and recommended)
connection limit of 10k.
ACID(Atomicity - Y, Consistency -
Y, Isolation - Y, Durability - Y).
99 1.98
Transactions 1%
No. Transactions are ACID at
document level.
33 0.66
Referential Integrity 1% No 33 0.66
Revision Control 1% Yes 99 1.98
Secondary Indexes 4% Yes 99 1.98
Composite keys 2% Yes 99 1.98
Full text search 2% Yes 99 1.98
Throughput 2% Better(Need number) 66 1.32
In-Memory 1%
Memcache is in-memory KV
store
99 1.98
Geospatial Indexes 1% Yes 99 1.98
Performance - 15%
Integrity - 10%

5. Relabalancing 1%
Initaite manually but cluster is
running and servicing requests
66 1.32
Latency 2% low latency 66 1.32
Replication
Architecture
5%
Multi-master replication and
replica sets. Couchbase supports
two types of replication. For intra-
datacenter clusters, Couchbase
uses membase-style replication,
which favors immediate
consistency in the face of a
network partition. For multi-
datacenter deployments,
CouchDB’s master-master
replication is used.
99 1.98
Horizontal Scaling /
Sharding(Share
Nothing)
Scoring: Auto Shard,
Shard Manually, No
Sharding
10% Yes. Autosharding. Hash. 99 1.98
Operating System 3% No Support yet for SuSE 66 1.32
Performance - 15%
Infrastructure
Scaling - 15%

6. Mangement /
Monitoring GUI
3% GUI and CLI 99 1.98
Documentation 3% Good 66 1.32
Backup / Recovery 3% Not real time 33 0.66
Engineering &
Installation
3% Easy 99 1.98
Cost and ROI 3% Reasonable Price point 33 0.66
Customer Base 3%
350 Customers total. Over 9500
paid servers are in use by several
indutries veritical.
66 1.32
License 3%
Apache(Community edition),
Proprietary(Enterprise edition)
66 1.32
Professional Support 3% Evolving 66 1.32
Operational
Adaptability - 15%
Cost and Market
Direction - 15%

7. Technology Depth
& Competition
3%
Market depth is limited to Key
Value database. Huge
competition is mounting from
MongoDB
33 0.66
Total Score 100% 63
Cost and Market
Direction - 15%

8. Desc Score WS Desc Score WS Desc Score
Basic unit of organization is
document storage, encoded in
JSON, XML, Text or binary.
Everything is compressed into
binary trees based on Xpath
Data model technique.
99 1.98
Document database,
schemaless using BSON(and
added JSON later). Used by
ADP for mobile solution
across 17 countries for mm+
customers. Trying to
introduce search
functionality
99 1.98
Leverages the Oracle
Berkeley DB Java Edition
High Availability storage
engine to provide
distributed, highly-available
key/value storage for large-
volume, latency-sensitive
applications or web services.
99
It is a document-centric,
transactional, search-centric,
structure-aware, schema-
agnostic, XQuery- and XSLT-
driven, high performance,
clustered, database server.
66 1.32
If you prefer to define
indexes, not map/reduce
functions. Cannot be used for
OLTP. Good for document
storage and retrieval not for
almost realtime applications.
Scaling becomes complex.
66 1.32
Provides fast, reliable,
distributed storage to
applications that need
to integrate with ETL
processing.
66
Government, Publishing,
finance and many other large-
scale sectors such as Medicare
and Medicaid services, Dow
Jones, Federal Aviation
Administration.
66 1.32
can easily replace RDBMS
with no schema so faster and
no predefined columns, good
for datastore, CRM
applications
99 1.98
Social networks, Online
retail, Web applications,
Backup services for mobile
devices.
99
Document stores, Native XML
DBMS.
66 1.32 Document 66 1.32 Distributed Key-Value store 66
MarkLogic MongoDB Oracle NoSQL

9. Role-based security features
JSON Storage
Direct use of HDFS
Multiple indexing strategies
ACID Consistency
Kerberos/LDAP support
66 1.32
Consistency
Partition Tolerance
Persistence
99 1.98
No single point of failure
Multi-Node backup
Optimized Hardware (Oracle
Big Data appliance)
Predictable latency
99
Native XML DBMS, Documents
stored as compressed binary
trees.
66 1.32 Memory Mapped files 66 1.32
Stored as key-value pairs,
which are written to
particular storage node(s),
based on the hashed value of
the primary key.
66
Yes 99 1.98 yes 99 1.98 Yes 99
Search includes many features
listed in the comment Although
many features are there, Solr /
Elastic Search integration is still
an involved exercise
66 1.32
Building search capability.
MongoDB has a drive to
integrate with Elastic Search
66 1.32 No 33
Data is stored as compressed
binary trees.
99 1.98 yes 99 1.98 No (Need to clarify) 33
Yes 99 1.98 Yes 99 1.98 Yes 99
Yes ( Need to clarify) 99 1.98 Yes 99 1.98 Yes (Need to clarify) 99
Yes (Supports for semantics in
that MarkLogic can store RDF
triples, using SPARQL as its
query language.)
66 1.32 No 0 0 Yes (RDF Graphs) 66

10. Xquery, JSON, Java API, REST,
XML
99 1.98
API calls, JavaScript, Rest.
Hadoop Connectior to and
from HDFS.
99 1.98 Java/C API 66
C++ 66 1.32 C++ 66 1.32 Java 66
JSON 66 1.32
Better handling of
documents, collections
99 1.98 Yes 99
XDMP (X Display Manager
Protocol)
66 1.32 Custom, binary (BSON) 66 1.32 TCP(RMI), TCP(Proprietary) 66
Can use C++ to do Map/Reduce
functions/calculations.
33 0.66 yes 66 1.32
Can use MapReduce when
integrated with Hadoop
environment
66
ACID, MVCC, No single point of
failure
99 1.98
Not MVCC but you can
sepratey use Mongo MVCC
99 1.98 ACID 99

11. Yes, need more information on
what transactions are included.
ACID.
99 1.98
MongoDB does not support
multi-document
transactions. However,
MongoDB does provide
atomic operations on a single
document. D ( A -
Conditional, C - Yes, Two
phased commit is required.
Uses memory mapped files
for data storage, I - N) 99 1.98
Provides ACID complaint
transactions for full Create,
Read, Update and Delete
(CRUD) operations, with
adjustable durability and
consistency transactional
guarantees. ACID.
99
Yes 66 1.32
No. Transactions are ACID
only at document level.
33 0.66 Yes 99
Yes ( Need to clarify) 66 1.32 No 33 0.66 No 33
Yes 99 1.98 Yes 99 1.98 Yes 99
Yes 99 1.98 Yes 99 1.98 Yes 99
Yes 99 1.98 Yes 99 1.98 Yes 99
Yes 99 1.98 No 99 1.98 No 0
Throughput is average 66 1.32 OK(Need number) 33 0.66 Better (Need number)_ 33
In-Memory stands can be
configured
66 1.32 Memory Mapped files 66 1.32 Not in-memory 33
Yes 66 1.32 Yes 99 1.98 No (Need verification) 33

12. Yes 33 0.66
Initiate manually but cluster
needs to be pulled down
33 0.66 Automatic Rebalancing 66
Average Latency ranges about
1.2ms
66 1.32 high at >20k 66 1.32 Low latency 66
Flexible Replication (Maintains
copies of data on multiple
servers. Original content is
created by an application on
master server. Replication
copies that content to one or
more replicas. Master and
replicas are in different clusters
which may or may not be in
same location. It is
asynchronous. Not a multi-
master replication as
documents updated by each
application must be in different
domains or this may cause
unpredictable behavior due to
overlap.)
66 1.32
Master-Slave-Replication for
more than 12 nodes, Replica
set is the preferred method,
need arbiters or a separate
machine and odd number for
replication
66 1.32 Master-Slave Replication 66
Yes. Distributed architecture
makes it easy to scale.
99 1.98
Yes. Scale Manually. Hash &
Range.
66 1.32 Yes. Autosharding. 99
Windows, Solaris, Linux, OS X 99 1.98
Solaris, Linux, Windows,
Mac OS X
99 1.98
Linux,OS X, Windows
99

13. Administration GUI 66 1.32
Monitoring GUI than
Management GUI
66 1.32
Provides proprietary, SNMP
and JMX based protocols for
monitorability of the cluster.
The proprietary protocols are
supported via browser
based and CLI interfaces
66
Reasonable Documentation 66 1.32
Good. There is a general
resistence in Enterprises
for MongoDB.
66 1.32 Excellent documentation. 99
Backup & Recovery are good.
Even point in time recovery
can be done
99 1.98
Providers a GUI to run the
backup. MMS Backup
Service.
99 1.98
Details are not investigated
but can be recovered
66
It is relatively easier to engineer
and deploy MarkLogic
33 0.66 Easy 33 0.66
Excellent documentation
helps to engineer swiftly
99
Very High Price Point 33 0.66 Fair. 66 1.32
Oracle products are generally
moderately priced if not
expensive.
66
No information on the customer
base
33 0.66
It is expanding its customer
base. 31% of customers
only reported no issues
according to Gartner.
66 1.32
This is evolving in Oracle and
no information on customer
base.
33
Commercial Licensing
(Restricted free version is also
available)
66 1.32
AGPL(Drivers:Apache).
Enterprise Licensing gets
costlier for bigger
enterprise.
66 1.32 AGPL 3 99
Evolving 66 1.32
Excellent Professional
Support
99 1.98 Fair. 66

14. Gartner's report indicates the
company is moving in multiple
technology direction and
may make the resources too
thin.
33 0.66
Fast Evolving into Mature
Model and depth in one
single database solution.
MongoDB is aggressively
expanding the
partnership. But
MongoDB is not
effectively putting
barries to stop the
competition.
99 1.98
Broader Market and Depth
in Database Technology
99
61 64

15. WS Desc Score WS Desc Score WS
1.98
key-value datastore mostly used
as in-memory DB and pub-sub
mechanism. Extremely fast
compared to others but limited
by RAM and easiest to configure
for small applications. No mobile
support
99 1.98
Open-source, fault-tolerant key-
value NoSQL database
implementing principles from
Amazon's Dynamo paper
influenced by CAP Theorem.
99 1.98
1.32
For rapidly changing data with a
foreseeable database size (should
fit mostly in memory). OLTP and
you can have a separate
persistence DB or datawarehouse
66 1.32
Distributed database designed to
deliver maximum data availability
by distributing data across multiple
servers across multiple data
centers. High Resiliency due to
server failure or network partition.
99 1.98
1.98
Stock prices. Analytics. Real-time
data collection. Real-time
communication. And wherever
you used memcached before.
66 1.32
Content Management, Social
applications, High Read/Write,
simple applications.
66 1.32
1.32 Key-Value inmemory 99 1.98 Distributed Key-Value Store 66 1.32
RiakRedisSQL

16. 1.98
in-memort data structure store,
Blazing fast
99 1.98
Own distributed full-text search
engine with robust query language
Fault-tolerant availability
Queries
Predictable latency
Operational simplicity
99 1.98
1.32 Volatile memory, File System 99 1.98
Uses a simple key/value model for
object storage. Objects in Riak
consist of a unique key and a value,
stored in a flat namespace called a
bucket. You can store anything you
want in Riak: text, images,
JSON/XML/HTML documents,
user and session data, backups, log
files etc.
66 1.32
1.98 Yes 99 1.98 Yes 99 1.98
0.66
Possible to integrate with app
coding(Need confirmation)
33 0.66
Native Search as well as Solr can be
used
66 1.32
0.66 Yes 99 1.98 Utilizes LevelDB for compression. 99 1.98
1.98 Yes 99 1.98 Yes (Need to clarify) 99 1.98
1.98 Yes 99 1.98 Yes ( Need to clarify) 99 1.98
1.32 No 0 0
Yes (Supports for semantics in that
MarkLogic can store RDF triples,
using SPARQL as its query
language.)
66 1.32

17. 1.32 API calls, Lua 66 1.32
Has official drivers for Ruby, Java,
Erlang, Python, PHP, and C/C++
99 1.98
1.32 C 66 1.32
Erlang, C, C++, some JavaScript,
MapReduce
99 1.98
1.98 Yes can be used 66 1.32 JSON 66 1.32
1.32 Telnet-like, Binary safe 66 1.32
Utilizes PBC (Protocol Buffer
Clients)interface, HTTP
66 1.32
1.32 No 0 0 Yes 66 1.32
1.98
Atomicity and consistency can be
guaranteed for a group of
commands with a server-side Lua
script.
Isolation is always guaranteed at
command level, and can also be
guaranteed for a group of
command using a MULTI/EXEC
block or a Lua script.
Durability can be guaranteed
when AOF is activated (with
systematic fsync). Can be SPOF
66 1.32
CAP Theorem (Consistency,
Availability, Partition tolerance
(failure tolerance).) Riak focuses on
Availability and Partition tolerance
and falls more on the "eventually
consistent" category. The theorem
states only two out of the three
properties can be fully relied on at
any time.
66 1.32

18. 1.98
Atomicity and consistency can be
guaranteed for a group of
commands with a server-side Lua
script.
Isolation is always guaranteed at
command level, and can also be
guaranteed for a group of
command using a MULTI/EXEC
block or a Lua script.
Durability can be guaranteed
when AOF is activated (with
systematic fsync)
AI(C- Eventual Consistency -
store to another DB, D- No, data
is lost if hard disk crashes. Used
to store specific time period data)
99 1.98
Does not support ACID
transactions. ID (A - N, C -
Eventually consistent)
66 1.32
1.98 Yes 99 1.98
No (As of Riak 1.4, counters were
released to allow developers to
build more complex functionality
on top of data stored as keys and
values.)
33 0.66
0.66 No 33 0.66 No 33 0.66
1.98 No 33 0.66 Yes 99 1.98
1.98 No 33 0.66 Yes 99 1.98
1.98 No 33 0.66 Yes 66 1.32
0 No 33 0.66 Yes 99 1.98
0.66In memory implementation can give high throughput66 1.32 Fair 66 1.32
0.66 In-Memory 99 1.98 Insall the memory Backend 66 1.32
0.66 It is doable 66 1.32 Possible 66 1.32

19. 1.32 Some overhead involved 33 0.66 Needed 33 0.66
1.32 Fair 33 0.66 Write latency is poor 33 0.66
1.32
Master-Slave replication,
Automatic failover
66 1.32
Multi-Datacenter replication(Multi
Master or Master Slave?)
66 1.32
1.98 No 33 0.66
Has a pluggable backend for its
core shard-partitioned storage,
with the default storage backend
being Bitcask. Schemaless design
allows more scalability ease.
66 1.32
1.98
Unix-like OS(*NIX), Mac Os X,
Windows
99 1.98
Windows, Solaris, Linux, OS X,
BSD
99 1.98

20. 1.32 Redis Admin UI 66 1.32
Many open source, self-hosted,
and service-based solutions for
aggregating and analyzing statistics
and log data for the purposes of
monitoring, alerting, and trend
analysis on a Riak cluster.
33 0.66
1.98 Very Little 33 0.66 Good 33 0.66
1.32
Backup can be done by various
ways
33 0.66
Backups could be inconsistent
which will be corrected by read
repair
33 0.66
1.98 Relatively involved process 33 0.66 Some efforts are involved 33 0.66
1.32 Low 33 0.66 Low 33 0.66
0.66 Moderate 33 0.66
30% Fortune 500 Companies uses
it. They also develop and contibute
drivers.
99 1.98
1.98 BSD-License 99 1.98
Apache Licensing 2.0 ( Open
Source)
66 1.32
1.32
Need more details but appears to
be pretty established
33 0.66 Reasoable 33 0.66

21. 1.98
Potentially competion from
CouchBase, MongoDB, Oracle
NoSQL
33 0.66
The scope is limited to No-SQL Key-
value product only so the
company's prospect in the broader
DBMS market will be very limited.
Oracel aggressive entry into this
market could be challenging key-
value space.
33 0.66
62 51 57