DBMS > Couchbase vs. Datomic vs. Fujitsu Enterprise Postgres vs. LMDB vs. Redis

System Properties Comparison Couchbase vs. Datomic vs. Fujitsu Enterprise Postgres vs. LMDB vs. Redis

Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

A high performant, light-weight, embedded key-value database library

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.

Primary database model

Document store

Relational DBMS

Key-value store

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

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store
Spatial DBMS

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	17.30
Rank	#36	Overall
	#5	Document stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

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

Website

www.couchbase.com

www.datomic.com

www.postgresql.fastware.com

www.symas.com/symas-embedded-database-lmdb

redis.com
redis.io

Technical documentation

docs.couchbase.com

docs.datomic.com

www.postgresql.fastware.com/product-manuals

www.lmdb.tech/doc

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

Developer

Couchbase, Inc.

Cognitect

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Symas

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2011

2012

2011

2009

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

1.0.6735, June 2023

Fujitsu Enterprise Postgres 14, January 2022

0.9.32, January 2024

7.2.4, January 2024

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

limited edition free

commercial

Open Source

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

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

C, C++, Go and Erlang

Java, Clojure

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
Windows

Linux
Unix
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

schema-free

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.

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

with RediSQL module

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Clojure
Java

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

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

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Transaction Functions

user defined functions

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

Triggers

yes

via the TAP protocol

By using transaction functions

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

none

But extensive use of caching in the application peers

partitioning by range, list and by hash

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

none

But extensive use of caching in the application peers

Source-replica replication

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

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

yes

Ephemeral buckets

yes

recommended only for testing and development

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
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Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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Licensing and pricing models

Core based licensing
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