DBMS > Elasticsearch vs. Fujitsu Enterprise Postgres vs. Riak KV vs. RocksDB

System Properties Comparison Elasticsearch vs. Fujitsu Enterprise Postgres vs. Riak KV vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

Distributed, fault tolerant key-value store

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Search engine

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Key-value store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Spatial DBMS

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.elastic.co/elasticsearch

www.postgresql.fastware.com

rocksdb.org

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.postgresql.fastware.com/product-manuals

www.tiot.jp/riak-docs/riak/kv/latest

github.com/facebook/rocksdb/wiki

Developer

Elastic

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

OpenSource, formerly Basho Technologies

Facebook, Inc.

Initial release

2010

2009

2013

Current release

8.6, January 2023

Fujitsu Enterprise Postgres 14, January 2022

3.2.0, December 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

C++

Server operating systems

All OS with a Java VM

Linux
Windows

Linux
OS X

Linux

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

schema-free

Typing

predefined data types such as float or date

yes

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

All search fields are automatically indexed

yes

restricted

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

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

HTTP API
Native Erlang Interface

C++ API
Java API

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

Erlang

Triggers

yes

by using the 'percolation' feature

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and by hash

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, using Riak Security

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