In-Memory Databases

In-Memory Databases Overview

In-memory databases (IMDBs), sometimes called in-memory data stores, are database systems that store, read, write, and access data in random access memory (RAM) instead of read only memory (ROM). IMDBs use RAM to quickly retrieve data by constantly making updated replicas of data records. IMBDs are defined by the location they keep data, not necessarily a type of data structuring As a result, both relational databases and non-relational databases can use in-memory database management systems.

IMDBs are an increasingly popular alternative to databases using traditional memory storage solutions like hard disk drives (HDDs) or solid state drives (SSDs). By storing data in RAM, IMBDs functionally avoid using the disk-based components in storage. This means that IMDBs can significantly reduce access response times, efficiently handle large traffic spikes, and scale to storage needs in real time. Compared to other database solutions, IMDBs can better support SQL, which generally performs better when it can utilize available volatile memory. These factors make IMDBs attractive options for business intelligence analysts, businesses with high internet traffic, and developers that need real-time caching.

Top Rated In-Memory Databases Products

TrustRadius Top Rated for 2022

These products won a Top Rated award for having excellent customer satisfaction ratings. The list is based purely on reviews; there is no paid placement, and analyst opinions do not influence the rankings. Read more about the Top Rated criteria.

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In-Memory Databases Products

(1-16 of 16) Sorted by Most Reviews

The list of products below is based purely on reviews (sorted from most to least). There is no paid placement and analyst opinions do not influence their rankings. Here is our Promise to Buyers to ensure information on our site is reliable, useful, and worthy of your trust.

SAP HANA Cloud

SAP HANA Cloud

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SAP HANA is an application that uses in-memory database technology to process very large amounts of real-time data from relational databases, both SAP and non-SAP, in a very short time. The in-memory computing engine allows HANA to process data stored in RAM as opposed to reading…

Microsoft SQL Server

Microsoft SQL Server is a relational database.

Redis™*

Redis is an open source in-memory data structure server and NoSQL database.

Key Features

  • Performance (69)
    100%
    10.0
  • Scalability (69)
    91%
    9.1
  • Availability (69)
    90%
    9.0
SingleStore (formerly MemSQL)

MemSQL is a NoSQL database offering from the company of the same name in San Francisco.

Amazon ElastiCache

Amazon ElastiCache offers fully managed Redis and Memcached.

Aerospike

The Aerospike Real-time Data Platform aims to enable organizations to act instantly across billions of transactions while reducing server footprint up to 80%. The vendor states Aerospike multi-cloud platform powers real-time applications with predictable sub-millisecond performance…

Redis Enterprise Cloud™*

Redis Labs in Mountain View, California offers Redis Enterperise Cloud, available on AWS, Microsoft Azure, and Google Cloud, delivered as a service and boasting maximal uptime, easy migration with on-prem deployments of Redis, designed to enable users to run any query, simple or…

Exasol

Exasol, from the company of the same name in Nuremberg, is presented by the vendor as a high-performance in-memory analytics database that aims to transform how organizations works with data, on-premises, in the cloud or both.

Kinetica

Kinetica, from the company of the same name headquartered in San Francisco, is an analytic database for fusing data across streams and data lakes to unlock value from spatial and temporal data at scale and speed. Kinetica helps companies drive outcomes from machine data that includes…

Memgraph

Memgraph is a tool that helps developers build modern, graph-based applications on top of streaming data in minutes, from the company of the same name headquartered in London.

VoltDB

VoltDB is an in-memory, scale-out NewSQL relational database from the company of the same name headquartered in Bedford, Massachusetts.

GridGain In-Memory Computing Platform

GridGain® provides an in-memory computing platform built on Apache® Ignite that enabless in-memory speed and massive scalability for data-intensive applications. It requires no rip-and-replace of existing databases and can be deployed on-premises, on a public or private cloud, or…

BrytlytDB

Brytlyt helps companies with thought analytics at scale. Brytlyt is a GPU accelerated database, analytics, and visualization workbench with in-platform AI capabilities and unique IP technology.

Apache Ignite

Apache Ignite™ is a distributed database for high-performance computing with in-memory speed

Hazelcast

Hazelcast is a real-time, intelligent application platform that enables enterprises to capture value at every moment by consolidating transactional, operational and analytical workloads into a single data platform.

Learn More About In-Memory Databases

What are In-Memory Databases?

In-memory databases (IMDBs), sometimes called in-memory data stores, are database systems that store, read, write, and access data in random access memory (RAM) instead of read only memory (ROM). IMDBs use RAM to quickly retrieve data by constantly making updated replicas of data records. IMBDs are defined by the location they keep data, not necessarily a type of data structuring As a result, both relational databases and non-relational databases can use in-memory database management systems.

IMDBs are an increasingly popular alternative to databases using traditional memory storage solutions like hard disk drives (HDDs) or solid state drives (SSDs). By storing data in RAM, IMBDs functionally avoid using the disk-based components in storage. This means that IMDBs can significantly reduce access response times, efficiently handle large traffic spikes, and scale to storage needs in real time. Compared to other database solutions, IMDBs can better support SQL, which generally performs better when it can utilize available volatile memory. These factors make IMDBs attractive options for business intelligence analysts, businesses with high internet traffic, and developers that need real-time caching.

In-Memory Databases vs. Embedded Databases

IMDBs are commonly conflated with embedded databases, but they are not strictly the same. IMDBs are defined by their usage of RAM for storage, but any database that is directly built into an application is considered an embedded database.

Embedded databases are useful for applications or programs that need to access stored data exceptionally fast, usually related to industry- or product-specific features and considerations. For example, many tax software products use embedded database systems to quickly access relevant information such as exemption calculations or previous year data. For these kinds of data access needs, an embedded database system may be a better choice than a standalone in-memory database.

Embedded databases typically use secondary memory for storage, but this isn’t always the case. An embedded database can also be an in-memory database, and vice versa. As such, each database system can utilize techniques typically found in the other.

In-Memory Database Features

The most common In-Memory Databases features are:

  • Data recovery
  • Support for big data and streaming data
  • Real-time data ingest
  • Real-time analytics
  • Visualization tools
  • High-speed transactions
  • Data versioning and history management
  • FIle management and monitoring
  • Job and queue management
  • Fault tolerance
  • Machine learning features and support
  • Deployment training and development
  • Scalability
  • I/O acceleration
  • Automated database integration
  • Automated data migration
  • Third party integration

In-Memory Databases Comparison

When choosing the best in-memory database for you, consider the following:

Integration vs. standalone: Depending on your current workflow, you’ll need to consider whether you want to purchase a standalone IMDB product, or if you want one that integrates with your current architecture. If you have an existing data management network, you will find that several vendors such as AWS offer connectors to make IMDB inclusion seamless and efficient. However, some vendors only offer IMDB as part of a larger service package, so these might be better for newer businesses or businesses looking to switch large parts of their workflows.

Open-source vs. managed: One of the major factors in choosing the best IMDB for you is determining whether you want an open-source or managed IMDB product. Open-source IMDBs are more flexible than their managed counterparts, and they are generally less expensive. However, managed IMDB vendors handle server uptime and general maintenance on behalf of the client, meaning that users will not need to manually address updating or troubleshooting.

Backup options: Because IMBDs store data in volatile storage, a process or server failure can result in lost data if appropriate backup solutions are not considered. Many IMBDs make version snapshots or operation logs that allow for a fairly quick recovery, but if data security is a primary concern, consider using an additional storage system. Most IMBDs include ways to automate data backup to an HDD or SSD, while a few can sync with cloud-based storage as well.

Pricing Information

There are many free in-memory databases, which tend to be open-source or significantly restricted versions of a vendor’s paid services. Pricing for paid services vary based on the amount of data stored, data security features, and other concerns. Contact a vendor to create an appropriate pricing model. Many vendors offer free trials or demonstrations of their product.

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Frequently Asked Questions

What do in-memory databases do?

In-memory databases are databases that store data in RAM rather than disk-based storage.

What are the benefits of using in-memory databases?

Because they use volatile storage sources, in-memory databases can access a large amount of data extremely quickly. In-memory databases are also easier to scale than many other databases, and as such can grow to handle a large amount of traffic and queries.

How much do in-memory databases cost?

There are many free, open source in-memory databases. For paid services, contact a vendor for a quote. Free trials and demos of paid services are common.