Scale Infinitely
Recover Quickly
Protect Broadly

Imanis Data (formerly Talena) is the only petabyte scale solution for backup and recovery and other data management use cases for modern data platforms.

Recover Your Data in Minutes Not Weeks

Don’t burn the haystack looking for the needle. Search and restore objects at a granular level using FastFind, a Google-style search interface backed by a powerful metadata catalog that scales to billions of objects. Restore points are fully self-describing with no dependence on prior full backups. The underlying storage layer ensures that data is intelligently shared among the available restore points without duplication, resulting in a highly optimized storage footprint.
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Petabyte Scale Agentless Architecture

Let go of past strategies for managing modern data platforms. The Imanis Data architecture easily adapts to the elastic nature of modern data platforms by scaling to thousands of nodes. Our agentless architecture completely eliminates cumbersome agent and listener management chores. An innovative, application-aware, incremental-forever technology tracks changes for both backups and restores to optimize data throughputs at petabyte scale.
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Machine Learning For Modern Backup and Ransomware Protection

Modernize your backup strategy with state-of-the-art machine learning algorithms for smart, RPO-driven policies and advanced protection against ransomware attacks and other anomalous behaviors. Search, query, and process your backed-up data in-place without requiring expensive, time-consuming restores. Get instant access to the processing power of open-source frameworks such as Spark, MlLib, and Elasticsearch.
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Cloud-Centric Data Backup Design

Imanis Data’s policy-driven architecture for modern block, object, and cold storage technologies offers seamless storage tiering at cloud scale. Native cloud support allows easy and transparent backup, recovery, and migration of data between diverse environments such as Microsoft Azure HDInsight and Amazon EMR. Guarantee safe and efficient usage of precious cloud resources with built-in, advanced encryption and compression capabilities.
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Reduce Your Data Storage Footprint by up to 80%

Handle the diverse, compressed file formats of modern data platforms using the industry’s only adaptive multi-stage storage pipeline. Ensure deduplication across all of the data being managed via our universal dictionary that scales to thousands of nodes. A dynamic combination of de-duplication, aggressive compression, and erasure coding results in a highly dense and compact storage that can reduce the storage footprint of modern web-scale data repositories by up to 80%.
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Latest News and Blog

By: Hari Mankude November 15, 2017

Agentless and Cloud Computing

In an age where on-premises architectures and relational databases dominated, delivering data management via an agent-based approach made sense since compute infrastructures, network bandwidth and database/virtualized topologies didn’t change drastically.…

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By: Jay Desai November 09, 2017

Migrating Hadoop Data to Microsoft Azure - part 2

In the previous post, we discussed the different scenarios that enterprises face migrating data to and within Microsoft Azure. Imanis Data is tightly integrated with Microsoft Azure cloud services and…

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By: Sanjay Sarathy November 08, 2017

Migrating Big Data To Microsoft Azure

Migrating Big Data To Microsoft Azure The promise of cloud computing and the ability for enterprises to generate meaningful insights from massive data sets has led to an enormous interest…

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By: Jana Lass November 08, 2017

Publicly Traded Advertising Tech Company - Hadoop Case Study

Publicly Traded Advertising Technology Company A publicly traded ad-tech company needed a disaster-recovery (DR) and an archive solution for its growing 900-node Hadoop cluster. This cluster supports the company’s programmatic…

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By: Jana Lass November 08, 2017

International Stock Exchange - Hadoop Case Study

International Stock Exchange One of the world’s largest stock exchanges transitioned from an older data warehouse to one built on top of Impala and Hadoop. As part of this transition,…

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By: Jana Lass November 08, 2017

Fortune 100 Technology Company - Hadoop Case Study

Fortune 100 Technology Company Data Management A Fortune 100 technology company has deployed a 500 TB, 200-node Hadoop cluster in production. This cluster supports an interactive application that consumes data…

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By: Jay Desai November 08, 2017

Migrating Hadoop Data to Microsoft Azure Cloud

With the rapid adoption of Microsoft Azure cloud services for Hadoop, one of the challenges organizations face is migrating data to a newly provisioned Microsoft Azure cloud infrastructure.  Existing methods…

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By: Jay Desai October 30, 2017

Why Backing Up VMs of Your Hadoop Infrastructure is Misguided

The other day a customer asked us why they shouldn’t just back up the entire virtualized infrastructure that houses their Hadoop environment.  There is certainly the benefit of simplicity to…

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By: Jay Desai October 12, 2017

Critical Considerations for Hadoop Data Replication

Disasters in a Hadoop environment take various forms.  It could be a major natural disaster that takes out an entire data center, an extended power outage that makes the Hadoop…

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By: Hari Mankude September 27, 2017

Expansion of Microsoft Azure Support With Azure Data Lake Store Integration

With our 3.1 release we now support Azure Data Lake Store (ADLS) and we’ve made this version available via the Azure Marketplace.  With support for both Azure Blob Storage and…

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By: Sanjay Sarathy August 29, 2017

The Collision of Machine Learning and Ransomware

Europe’s recent wave of ransomware attacks put ransomware on the map for many, and heightened concerns for others. The latest attack, which goes by several names including Petya, Petrwrap and…

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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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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: Sanjay Sarathy August 09, 2017

Hadoop Backup eBook

Hadoop Backup eBook Critical requirements for data protection or backup in the world of modern data platforms include:   Incremental-forever backups Fast and granular recovery Parallel data transfers between the…

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By: Sanjay Sarathy August 09, 2017

Vertica Backup eBook

Vertica Backup eBook Critical requirements for data protection or backup in the world of modern data platforms include:   Incremental-forever backups Fast and granular recovery Parallel data transfers between the…

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By: Sanjay Sarathy August 09, 2017

Couchbase Backup eBook

Couchbase Backup eBook Critical requirements for data protection or backup in the world of modern data platforms include:   Incremental-forever backups Fast and granular recovery Parallel data transfers between the…

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By: Sanjay Sarathy August 09, 2017

Cassandra Backup eBook

Cassandra Backup eBook Critical requirements for data protection or backup in the world of modern data include:   Incremental-forever backups Fast and granular recovery Parallel data transfers between the primary…

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By: Sanjay Sarathy August 08, 2017

Three Customer Profiles for Modern Data Management

Three Customer Profiles for Modern Data Management This eBook highlights three customer profiles and associated use cases of the Imanis Data platform. These customers generated significant business benefits using Imanis…

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By: Sanjay Sarathy August 08, 2017

Slashing the TCO of Backup and Recovery

Slashing the TCO of Backup and Recovery This eBook will walk through some of the biggest opportunities to impact the total cost of ownership (TCO) of a data management infrastructure,…

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By: Sanjay Sarathy August 08, 2017

Vertica Datasheet

Highly Scalable Data Management for Vertica Vertica is an ideal database for large, rapidly growing data sets that require fast query performance. The database has seen great traction for mission-critical…

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By: Sanjay Sarathy August 08, 2017

Microsoft Azure Datasheet

Cloud Data Management in Microsoft Azure Support critical data management workloads in Microsoft Azure across diverse modern data platforms from HDInsight to NoSQL platforms like Cassandra, DataStax Enterprise, MongoDB and…

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By: Sanjay Sarathy August 08, 2017

MongoDB Datasheet

Highly Scalable Data Management for MongoDB MongoDB is one of the pioneers in the non-relational or NoSQL database market. With a vibrant developer community, companies worldwide have deployed MongoDB as…

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By: Sanjay Sarathy August 08, 2017

A Technical Perspective on the Imanis Data Platform

A Technical Perspective on the Imanis Data Platform Over the past decade, the emergence of social media, mobile, and cloud technologies has created vast quantities of data, or “Big Data”,…

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By: Jana Lass August 06, 2017

Hadoop Datasheet

Highly Scalable Data Management for Hadoop Hadoop has enabled companies to deploy large-scale, distributed applications that identify customer shopping patterns, tackle potential fraud, and even process human genome data across…

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By: Jana Lass August 06, 2017

Couchbase Datasheet

Highly Scalable Data Management for Couchbase Couchbase is at the forefront of the NoSQL movement and is deployed widely in organizations seeking to participate in and profit from the Digital…

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By: Jana Lass August 06, 2017

Cassandra/Datastax Datasheet

Highly Scalable Data Management for Cassandra and DataStax Enterprise The number of mission-critical applications built on top of Cassandra and Datastax Enterprise is rising rapidly. These applications enable companies to…

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By: Jana Lass August 04, 2017

Imanis Data Solution Brief

Reduce downtime by rapidly recovering data at various levels of granularity and save significant CapEx and OpEx via up to 80% reduction in storage footprint.

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By: Jana Lass July 31, 2017

An Inside Look into the Imanis Data Architecture

An Inside Look into the Imanis Data Architecture Big Data has matured beyond the confines of the research lab, and now serves as the foundation for high-value, business-oriented applications. Yet…

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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: 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: 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: 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: 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: 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 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: 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: 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: 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: 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: 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: 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: 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: 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 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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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Our Awards

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

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