DBMS > etcd vs. Fujitsu Enterprise Postgres vs. GridDB vs. RethinkDB

System Properties Comparison etcd vs. Fujitsu Enterprise Postgres vs. GridDB vs. RethinkDB

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Editorial information provided by DB-Engines

Name

Description

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

Scalable in-memory time series database optimized for IoT and Big Data

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Secondary database models

Document store
Spatial DBMS

Key-value store
Relational DBMS

Spatial DBMS

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

Score	7.05
Rank	#53	Overall
	#5	Key-value stores

Score	0.22
Rank	#304	Overall
	#137	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Website

etcd.io
github.com/etcd-io/etcd

www.postgresql.fastware.com

griddb.net

rethinkdb.com

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.postgresql.fastware.com/product-manuals

docs.griddb.net

rethinkdb.com/docs

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Toshiba Corporation

The Linux Foundation

since July 2017

Initial release

2013

2009

Current release

3.4, August 2019

Fujitsu Enterprise Postgres 14, January 2022

5.1, August 2022

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Apache Version 2

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.

Implementation language

C++

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

string, binary, float, bool, date, geometry

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

SQL

Support of SQL

yes

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

gRPC
JSON over HTTP

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

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

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

user defined functions

Triggers

yes, watching key changes

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID at container level

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

MVCC based

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

yes

users and table-level permissions

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

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