DBMS > GridGain vs. Hypertable vs. Redis vs. YottaDB

System Properties Comparison GridGain vs. Hypertable vs. Redis vs. YottaDB

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

GridGain is an in-memory computing platform, built on Apache Ignite

An open source BigTable implementation based on distributed file systems such as Hadoop

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

A fast and solid embedded Key-value store

Primary database model

Key-value store
Relational DBMS

Wide column store

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Key-value store

Secondary database models

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Relational DBMS

using the Octo plugin

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	155.94
Rank	#6	Overall
	#1	Key-value stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

www.gridgain.com

redis.com
redis.io

yottadb.com

Technical documentation

www.gridgain.com/docs/index.html

docs.redis.com/latest/index.html
redis.io/docs

yottadb.com/resources/documentation

Developer

GridGain Systems, Inc.

Hypertable Inc.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

YottaDB, LLC

Initial release

2007

2009

2001

Current release

GridGain 8.5.1

0.9.8.11, March 2016

7.2.5, May 2024

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

Java, C++, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

an inofficial Windows port is available

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Docker
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

with RediSearch module

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

with RediSQL module

by using the Octo plugin

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

C++ API
Thrift

proprietary protocol

RESP - REdis Serialization Protocol

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Lua; Redis Functions coming in Redis 7 (slides and Github)

Triggers

yes (cache interceptors and events)

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

selectable replication factor on file system level

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomic execution of command blocks and scripts and optimistic locking

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Security Hooks for custom implementations

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

Users and groups based on OS-security mechanisms

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