Industry-Leading Data Management Software for Hadoop

Data management for Hadoop - HDFS, Hive, HBase, HDInsight, Impala - helps you recover quickly in the event of data loss, deliver applications faster, minimize non-compliance risk, and archive old data.

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Data Management Software for Hadoop

Granular Backup and Recovery

Reduce downtime costs from ransomware or human errors through granular recovery via Imanis Data FastFind™. Recover down to the partition level, and significantly reduce operational costs via machine learning, smart storage optimization, and incremental-forever backups.

Faster Test Data Management

Deliver applications faster by rapidly moving copies of production data to engineering and DevOps teams. Meet compliance standards by masking confidential data.

Effortless Cloud Migration

Migrate your big data workloads with ease, whether you are moving from a completely on-prem deployment to the cloud, transitioning between cloud providers, or just want to run parts of your workload in the cloud.

Efficient Archiving

Reduce CapEx and OpEx costs, and support regulatory requirements, by moving older, less frequently used data to cost-efficient storage tiers such as Amazon Glacier.

Native Replication is Not Total Data Protection

While data replicas provide protection against node failure, the unfortunate reality is that built-in Hadoop replicas won’t protect your business in many common data loss scenarios. In the event of human error or application corruption, the error is propagated across replicas.

How confident are you with your backup strategy?

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How Does Imanis Data Compare to Native Hadoop Tools?

  • Faster and Easier Data Recovery

    No need for detailed specifics: locate the lost objects for recovery with ease using our FastFind technology.

  • Reliable and Resilient Backups

    Backups and archives that are resilient to hardware failure, and stored on a separate system or in the cloud.

  • Scalable and Flexible Infrastructure

    Highly scalable, multi-use case solution that minimizes the impact of Hadoop data loss, whether you’ve stored the data in HDFS, Hive, or HBase.

Related Resources

By: Hari Mankude August 18, 2015

Big Data Needs A New Backup Architecture - Part 1

Big Data refers to immense amounts of structured and unstructured data that cannot be processed by traditional databases and software techniques. Examples of Big Data platforms include NoSQL databases like…

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By: Hari Mankude August 25, 2015

Big Data Needs A New Backup Architecture - Part 2

In a previous post, I outlined the major requirements for backup in a Big Data world, including incremental-forever backups and fast, granular recovery. This post highlights additional requirements and summarizes…

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By: Srinivas Vadlamani September 01, 2015

Imanis Data and Data Masking

Imanis Data offers companies highly scalable data management software for NoSQL databases, Hadoop, and modern enterprise data warehouses. When such assets, or subsets of them, are deployed to smaller secondary…

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By: Jay Desai September 08, 2015

Data Management Challenges With Cassandra Databases

With the growing popularity of NoSQL databases (Cassandra, Couchbase, MongoDB, etc.), customers are generally comfortable running large-scale, mission-critical applications in production. Most of these applications are critical to the success…

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By: Jay Desai September 14, 2015

Recovery-Centric Data Management for Cassandra Databases

In my previous blog, I discussed some very important data management challenges with Cassandra databases. To address these challenges, Imanis Data has developed a software-defined storage product to manage data in…

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By: Shailesh Parulekar September 21, 2015

Robust Workflow Management for Big Data Workloads

Big Data refers to large-scale structured, semi-structured, or unstructured data sets whose manipulation and management present significant logistical challenges. Most of the Big Data platforms (Hadoop, NoSQL, etc.) run on…

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By: Phil Shelley September 29, 2015

Big Data and the Rise of the Enterprise Data Hub

The following guest post is from Dr. Phil Shelley. As former CTO of Sears Holdings, Dr. Shelley has several years experience in helping move a large iconic brand into a…

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By: Jay Desai October 15, 2015

Five Unexpected Use Cases for Vertica Backup and Recovery

The rapid adoption of technologies such as social media, mobile, Internet of Things, and the cloud has resulted in the creation of large amounts of data that need to be…

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By: Hari Mankude November 04, 2015

Why Is Imanis Data A Software-Defined Platform?

Software-defined secondary storage platform: That would be a mouthful if spoken, so let me explain what we mean by it and why we focused on building this architecture rather than relying…

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By: Shailesh Parulekar November 17, 2015

Understanding Replication Versus Backup in a Big Data Environment

When we talk with customers who are implementing Big Data technologies, we are often presented with two scenarios leading to two questions:   We have multiple replicas of data on…

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By: Srinivas Vadlamani January 06, 2016

Four Advantages of Using Imanis Data for Vertica Backup and Recovery

As the architect for Imanis Data’s Vertica integration, I’ve helped a number of customers protect critical business data stored in Vertica. I’ve noticed that a number of Imanis Data’s capabilities are highly…

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By: Sanjay Sarathy January 19, 2016

The Big Opportunity for Big Data in Healthcare

Last week, I attended a great discussion on Big Data and life sciences, hosted by FierceBiotech and held in conjunction with the J.P. Morgan Healthcare Conference. The panel, moderated by FierceBiotech Editor-in-Chief John Carroll,…

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By: Hari Mankude January 26, 2016

Optimal Data Management Strategies in the Cloud

The next-generation architecture to provide data protection for scale-out, mission-critical databases, such as Apache Cassandra, requires key features like incremental-forever, granular, and fast recovery, Such a solution must also act…

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By: Robin Schumacher March 02, 2016

NoSQL and Data as Business Currency

The following guest post is from Robin Schumacher, Vice President of Products at DataStax.    With data doubling every two years and only 0.5% of that data currently analyzed companies…

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By: Sanjay Sarathy April 19, 2016

Ransomware and Your Big Data Backup Strategy

The latest security threat making news almost every day is ransomware, a virus that prevents users from accessing computers and information systems till money is paid. That virus has been…

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By: Jay Desai June 16, 2016

Four Big Mistakes In a Modern Data Management Architecture

As enterprises deploy in greater numbers big data platforms like NoSQL, Hadoop and enterprise data warehouses, it is clear that certain data management architectures limit a company’s effectiveness to protect…

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By: Srinivas Vadlamani July 06, 2016

Announcing Our Couchbase Integration

Like our other existing integrations, our Couchbase support enables us to provide an extremely feature-rich and enterprise-scale backup, recovery and test data management solution.   My co-founder has discussed in detail the differences…

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By: Sanjay Sarathy August 15, 2016

The Changing Role of the Modern Database Administrator

As enterprises increasingly implement NoSQL database technologies like Couchbase and Cassandra, and Hadoop database components like HBase and Hive, the responsibilities of maintaining and administering these modern data platforms often…

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By: Jana Lass October 11, 2016

A Nightmare on Data Street

The story you are about to read is a dramatic telling of a tale of data loss; the names and companies have been changed to protect the identity of the…

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By: Jana Lass October 18, 2016

Data-Razer

The story you are about to read is a dramatic telling of a tale of data loss; the names and dates have been changed to protect the identity of the…

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By: Jana Lass October 25, 2016

MURD3R BY P0RT NUM8ERS

This is the third in our “Data Loss Horror Stories” series, the others being Nightmare on Data Street and Data Razer. It is a dramatic telling of a tale of data loss; as…

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By: Hari Mankude December 12, 2016

The Limitations of Snapshots for Cassandra Backup

Cassandra snapshots are often used to help customers go back in time to recover from a badly written command or an issue arising from application corruption. However, there are two…

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By: Hari Mankude December 20, 2016

Data Recovery Challenges With Cassandra Snapshots

In a prior blog post I described some of the storage and management overhead challenges of using Cassandra snapshots as part of your strategic data protection policy. In this post, I’ll…

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By: Jay Desai January 12, 2017

Protecting and Mirroring Databases In The Cloud

Summary: A leading provider of Data as a Service for data-driven enterprise applications turned to Imanis Data to protect its critical customer data assets stored in Cassandra and to enable rapid…

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By: Jay Desai January 25, 2017

Reducing Backup Storage Footprint & Simplifying Recovery

This is the second in a series on customer deployments with Imanis Data. The first describing a customer deployment scenario in AWS is highlighted here.   Summary: A large business and financial…

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By: Nitin Donde January 27, 2017

Looking Back and Forward: The State of Enterprise Data Management

2016 was an excellent year for Imanis Data. We saw significant enterprise traction and now have over a thousand big data nodes and several petabytes under management. Most importantly, we…

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By: Nitin Donde February 02, 2017

Looking Back and Forward: Part 2

In my previous post I highlighted some of our key accomplishments and the lessons we learned in 2016. In this post, I want to focus on the key trends we anticipate driving…

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By: Jay Desai February 13, 2017

Data Protection For An Analytics Data Warehouse

This is a continuation of our series highlighting why and how customers are deploying Imanis Data. Others in this series are here and here.   Summary: A leading online travel brand deployed Imanis Data…

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By: Hari Mankude March 06, 2017

Two Under-Appreciated Imanis Data Capabilities

Recently I have spent a lot of time working with existing customers to understand their requirements and help them take full advantage of the Imanis software for their modern data…

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By: Jay Desai March 13, 2017

Data Protection in a Complex Hadoop Deployment

Summary: One of the world’s largest financial services companies deploys Imanis Data to protect their Hadoop data lake and support business-critical analytics capabilities.   Industry: Financial Services. One of the largest financial…

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By: Sapan Maniyar March 30, 2017

The Unique Capabilities of the Imanis Data HBase Connector

In this post we compare the Imanis Data HBase Connector with existing and proposed data protection solutions for Apache HBase. Imanis Data HBase connector design As with all Imanis Data…

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By: Sanjay Sarathy April 12, 2017

What’s Next With Big Data: A Q&A with ONSET’s Shomit Ghose

ONSET Ventures General Partner Shomit Ghose has witnessed and invested in a variety of major technological disruptions ranging from SaaS and cloud, to Big Data and next generation security. In…

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By: Jay Desai April 18, 2017

Backing Up and Restoring Very Large Data Streams

In this post, we highlight how Imanis Data helped an industrial manufacturer protect a very large DataStax Enterprise environment that is hosted in AWS.   Summary: A leading industrial manufacturer makes…

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By: Hari Mankude May 04, 2017

Cloud Data Management at Exabyte Scale

Earlier this year I hosted a webinar that discussed the key data management challenges enterprises face when running or migrating big data workloads to the cloud. These workloads are moving in…

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By: Sanjay Sarathy August 09, 2017

Imanis Data 3.0: Machine Learning, New Data Platforms & Even Faster Performance

When we launched two years ago, the need to support companies building mission-critical applications on top of modern data platforms like Cassandra, Couchbase, Hadoop, MongoDB and Vertica was growing fast.…

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By: Nitin Donde August 09, 2017

Introducing Imanis Data

When my co-founders and I first came together in 2013 to discuss what would become Talena, our mission was clear: help companies minimize the impact of data loss in today’s…

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Through Reltio data-driven applications business users access and expect constant availability of this data. Imanis Data's backup, recovery and test data management solution is an ideal fit for our rapidly growing DataStax Enterprise environment, and their recent security and AWS S3 enhancements are critical for our customers, particularly in highly regulatory environments.

Zoltan Gombosi

Vice President, Engineering

The rapid rise of big data applications is changing how companies protect and manage the availability of data throughout the application life cycle -- concurrently we are acutely more aware of the tremendous business value that all data holds.

Nik Rouda

Senior Analyst, Enterprise Strategy Group

If you thought the need for backup somehow evaporated with the advent of Hadoop, its probably because you don't really understand backup.

Robin Bloor

Co-Founder & Chief Analyst

Business applications built on top of modern data platforms such as MongoDB and Cassandra are just as exposed to the threat of ransomware and critical data loss as traditional applications. Yet, many IT managers are just beginning to look at data protection requirements for these applications. IT organizations need to consider data protection tools designed specifically for these environments, such as Imanis Data, because some of the underlying architectural issues are different from traditional data types.

Phil Goodwin

Research Director

Speed and efficiency of recovery is vitally important in helping us achieve our business goals. We’ve found that Imanis Data 3.0 is the only platform that can easily scale with our growing business and data needs. Its rapid backup and recovery capabilities have reduced our potential downtime to a minimum and have helped our business run more efficiently.

Rodrigo Balan

Network Operations Manager

When we moved to a Big Data architecture, we knew that application and data recovery was a fundamental requirement. Where most companies fall short, Imanis Data provides that at scale.

Kersi Tavadia

CIO

Don’t Learn The Hard Way!

Prior to implementing Imanis Data, one Fortune 10 customer learned the hard way how costly losing data can be. A single developer error caused the loss of 400TB of data in their Hadoop environment. They spent nearly four weeks rebuilding this data set and it cost the company over $1 million in direct and opportunity costs. They now use Imanis Data as a highly scalable data protection platform that provides backup and recovery across their Hadoop infrastructure.

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