Enterprises are adopting a more data-centric approach as distributed applications like IoT, mobile, and cloud have become more prevalent. This has led to a rise in open-source and scale-out databases that have different data management needs than traditional relational databases. Specifically, these newer databases require recovery tools that can handle the scale-out nature and flexibility of deployment in private and public clouds. Datos IO has introduced a distributed versioning platform to address these new recovery needs for databases like Cassandra and MongoDB. Their platform offers features like cluster-wide consistency across versions, semantic deduplication to reduce storage usage, and "repair-free" automated recovery without manual steps.

1. Enterprises are embracing
a data-centric world
For 30 years, relational databases ruled
the client-server world. Veritas and
Legato (EMC) provided much-needed
data management tools.
Now, distributed applications (IoT,
mobile, social, cloud) demand a new
data-centric world where 5 of the top 10
databases are open-source or scale out.
Enterprises must be able to recover
corrupted or inaccurate data.
Next-gen databases need
recovery tools for application
admins and DevOps.
Although adoption of these scale-out data stores has been rising, customers
need enterprise-grade recovery products that are built from the ground up for
next-generation applications. In this new data-centric world of distributed and
composite applications deployed on heterogeneous data stores, everything
about recovery is changing:
• CIOs and CSOs are driving new business requirements to
capture more value from data.
• Application and database architects have new recovery requirements
given the scale-out nature of these data stores.
• DevOps are the new consumers of recovery products.
• IT ops expect flexible deployment models in private and public clouds.
Most scale-out databases do offer capabilities such as cross-datacenter replica-
tion, but these capabilities address availability requirements only. They do not
provide point-in-time versioning and recovery, so enterprises cannot go back
and fix operational errors. In fact, if errors are introduced, the databases’ multi-
node replication can lead to almost immediate corruption across all nodes of the
enterprise’s data center.
The enterprise data center is embracing a data-centric world to support the
social, mobile, and cloud environments in which today’s consumers live. The
volume, ingestion rate, and real-time nature of distributed applications is driving
the adoption of scale-out data stores such as Cassandra, MongoDB, Google
BigTable, Amazon DynamoDB, and others.
Datos IO Product Overview
The Industry-First Distributed Versioning Platform
for Scale-Out and Cloud Databases

2. The Datos IO Versioning Platform:
Overview And Features
Datos IO is introducing the industry’s first distributed versioning platform for
scale-out databases, starting with Cassandra and MongoDB, that empower
application architects and DevOps with ease of deployment and usability. The
first version of the Datos IO product introduces several pioneering features,
including:
Cluster-wide consistency: Cluster-consistent versions can be
for any point in time and are designed for elastic-RPO needs (as
low as 15 minutes to hours). The versions can be coarse or fine-
grained, are fault resilient, follow the application-defined quorum
(any, all, majority), and are always stored in native format.
Semantic deduplication: This industry-first deduplication tech-
nology is built from ground up for scale-out, eventually consistent
databases. Semantic dedpulication extends the traditional notion
of deduplication to also include semantic equivalents of data
values. This technology drastically reduces the storage capacity
(cost) required to maintain versions. Combined with integrated
delta tracking, it also significantly reduces the versioned storage
footprint.
Orchestrated “repair-free” recovery: Users can restore an entire
keyspace/database or a single column family/collection without
manual admin steps. No copying, no scripts, no chance of manual
error and, most of all, no repair. Datos IO versions are in native
format and database-consistent, so no repair is required
on restore.
Scale-out recovery platform: Big Data and cloud databases have
scale-out architectures because they are built to handle extreme
throughput requirements; the data recovery platform needs to
scale horizontally with the data stores. The Datos IO platform
grows horizontally with application recovery needs, from a single
node to a scale-out Datos IO cluster.
The Datos IO Early Access Program (EAP) is available today, with general avail-
ability expected in 2016. Learn more at www.datos.io.
Datos IO
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Recovery Reinvented
Breakthrough features built
from the ground up for the
new data-centric world