A few years ago, I started exploring the new breed of distributed databases or “Big Data Databases” as they are popularly called, and the possibilities they have opened in the field of database management systems. What I liked about these databases was the abstraction they created over distributed storage systems. I thought that these new breeds of distributed databases opened an opportunity to develop a next generation of RDBMS, which are as functional as relational databases and as scalable as distributed databases.

Around the same time, words like “NoSQL” started gaining momentum. Although NoSQL means "Not Only SQL", Big Data Databases did not actually support any SQL in the beginning. Since then, many of the Big Data Databases have added support for some form of basic SQL. While such basic support is a good start, they still lack comprehensive standards-based support for relational data modeling and SQL. I thought: why not build this functionality on top of Big Data Database platforms? Afterall, relational theory and SQL are just functional specifications. So instead of abandoning these concepts, how about building on top of it?

Data relationships are intrinsic to the business functionality of the application. When the applications get complex, the organizations using Big Data Databases start using some kind of meta-data driven approach to manage the data relationships - without even realizing that they are creating a pseudo-RDBMS.

I think that the new breed of Big Data Databases are great tools to create the next generation of RDBMS. The future of the database technology will be all about the tools which: (a) extrapolate proper strategy for storing and accessing data on the underlying Big Data Database platforms based on the relational data model, and (b) expose it via SQL and standard based interfaces like JDBC. This is the logical next step.

At Cloud2DB, we have already taken that logical next step and created a framework to implement a standards based access layer over any Big Data Database platform. Typically, just by implementing one standard interface, you will be able to make any Big Data Database accessible via Relational Model, SQL and JDBC. Cloud2DB is truly a framework based on distributed architecture. It supports the distribution of the various parts of the data model across different Big Data Databases. We can demonstrate the power and the ease of use of the framework with our implementations for major Big Data Databases like Cassandra, MongoDB, CouchDB and even in- memory databases like Reddis. We have just added support for Google Cloud Database products Spanner, Bigtable, Firestore, Memorystore, Amazon AWS Database products DynamoDB, DocumentDB, MemoryDB, Keyspaces and Azure Database products CosmosDB-NoSQL, CosmosDB-MongoDB, CosmosDB-Cassandra, Tables

Sandeep Sathaye

Founder and Principal

A seasoned technologist with 30 years of hands-on expertise in translating business needs into technology. Trusted advisor to business executives and clients.



Cloud2DB is a universal database for Big Data computing. Cloud2DB allows for an immediate adoption of Big Data Database technologies into your enterprise technology stack. This is truly a plug-and-play into the Big Data database technologies.

What is it?

Cloud2DB is a framework that brings Relational Database functionality to Big Data Database platforms by bridging the gap between Big Data Database technologies and Relational Database technologies. Just by implementing one standard interface you should be able to make any Big Data Database accessible via Relational Model, SQL and JDBC. Cloud2DB works seamlessly with most of the popular Big Data Database technologies like Cassandra, MongoDB, Redis, CouchDB, Google (Spanner, Bigtable, Firestore, Memorystore), Amazon (DynamoDB, DocumentDB, MemoryDB, Keyspaces) and Azure (CosmosDB-NoSQL, CosmosDB-MongoDB, CosmosDB-Cassandra, Tables) It also supports the Relational Database standards, ANSI SQL-92/ANSI SQL-99 and JDBC 3.0. It removes the technology lock-in which people fear the most about when adapting to emerging Big Data Database technologies.

What sets us apart?

Although there are many Big Data Databases that offer better performance and scalability, they lack the built-in support for standards, structure and interoperability that is required to implement enterprise class applications effectively and quickly. This is where Cloud2DB excels. Cloud2DB provides a standards-based abstraction layer over these Big Data Databases to provide you with performance and scalability of Big Data Databases along with structure, standards, and interoperability of Relational Database platforms. Cloud2DB is truly a framework based on distributed architecture. It supports the distribution of the various parts of the data model across different Big Data Databases.


  • Bigdata database support
    • Cassandra
    • MongoDB
    • CouchDB
    • Reddis
    • Google Spanner
    • Google Bigtable
    • Google Firestore
    • Google Memorystore
    • Amazon DynamoDB
    • Amazon DocumentDB
    • Amazon MemoryDB
    • Amazon Keyspaces
    • Azure CosmosDB-NoSQL
    • Azure CosmosDB-MongoDB
    • Azure CosmosDB-Cassandra
    • Azure Tables
  • Bigdata database integration
    • Software framework to integrate new Bigdata databases
  • ANSI SQL-92/ANSI SQL-99 support
  • Referential integrity (Primary Keys, Foreign Keys)
  • Role Based Access
  • Joins (Inner Join, Left Outer Join, Theta Join, Cross Join)
  • Sub-queries (Exists, Not Exists, In)
  • DDL & DML
  • Local Transactions
  • Native Transactions, if supported by underlying database
  • JDBC 3.0 support
  • Tools support
    • All JDBC compliant tools
    • For example
      • Squirrel SQL (database management)
      • Power Architect (data modeling)
      • Jasper Reports (reporting)
  • Framework support
    • All JDBC compliant frameworks
    • For example
      • Hibernate (OR mapping)
      • Spring (Data access from application)

Product Architecture

The Bigdata databases mentioned in the top layer are just representative databases. Cloud2DB framework allows you to expose any Bigdata database via Relational, SQL and JDBC standards.

The products mentioned in the bottom layer are just representative products. Cloud2DB works with any JDBC compliant product.


With the experience we have gained on Bigdata technologies while developing our Cloud2DB product, we will provide your organization support on implementing Bigdata technologies in your organization.

Data integration

Integration of Bigdata databases into your enterprise technology stack.
This includes,
Bigdata databases like Cassandra, MongoDB, DynamoDB, CouchDB etc.
In-memory databases like Reddis, Amazon MemoryDB, Hazelcast etc.

Data architecture

Bigdata database architecture focused on performance and scalability for dealing with exceptionally large datasets.

API development

Development of APIs for Bigdata Database access.