DBMS > GridGain vs. InterSystems Caché vs. LevelDB vs. Redis vs. XTDB

System Properties Comparison GridGain vs. InterSystems Caché vs. LevelDB vs. Redis vs. XTDB

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

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

A multi-model DBMS and application server

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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 general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

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

Document 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

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.gridgain.com

www.intersystems.com/products/cache

github.com/google/leveldb

redis.com
redis.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.gridgain.com/docs/index.html

docs.intersystems.com

github.com/google/leveldb/blob/main/doc/index.md

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

www.xtdb.com/docs

Developer

GridGain Systems, Inc.

InterSystems

Google

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Juxt Ltd.

Initial release

2007

1997

2011

2009

2019

Current release

GridGain 8.5.1

2018.1.4, May 2020

1.23, February 2021

7.2.4, January 2024

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

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

Open Source

MIT License

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++

Clojure

Server operating systems

Linux
OS X
Solaris
Windows

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Illumos
Linux
OS X
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

depending on used data model

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

yes, extensible-data-notation format

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

with RediSearch module

yes

SQL

Support of SQL

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

yes

with RediSQL module

limited SQL, making use of Apache Calcite

APIs and other access methods

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

.NET Client API
JDBC
ODBC
RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

HTTP REST
JDBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C#
C++
Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

Clojure
Java

Server-side scripts

Stored procedures

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

yes

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

Triggers

yes (cache interceptors and events)

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts and optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 rights for users, groups and roles

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

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