DBMS > Geode vs. PostgreSQL vs. Riak TS vs. YTsaurus

System Properties Comparison Geode vs. PostgreSQL vs. Riak TS vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Key-value store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Time Series DBMS

Document store
Key-value store

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.21
Rank	#324	Overall
	#45	Document stores
	#48	Key-value stores

Website

geode.apache.org

www.postgresql.org

ytsaurus.tech

Technical documentation

geode.apache.org/docs

www.postgresql.org/docs

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

ytsaurus.tech/docs/en

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

PostgreSQL Global Development Group

www.postgresql.org/developer

Open Source, formerly Basho Technologies

Yandex

Initial release

2002

1989

1989: Postgres, 1996: PostgreSQL

2015

2023

Current release

1.1, February 2017

16.3, May 2024

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

BSD

Open Source

Apache License, Version 2.0

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

the JDK (8 or later) is also required

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
OS X

Ubuntu

Data scheme

schema-free

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like query language (OQL)

yes

standard with numerous extensions

yes, limited

YQL, an SQL-based language, is supported

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

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

HTTP API
Native Erlang Interface

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C
C++
Delphi
Java

JDBC
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++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Erlang

Triggers

yes

Cache Event Listeners

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

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.

yes

User concepts

Access control

Access rights per client and object definable

fine grained access rights according to SQL-standard

Access Control Lists

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