DBMS > Greenplum vs. Postgres-XL vs. SingleStore vs. TimesTen vs. YottaDB

System Properties Comparison Greenplum vs. Postgres-XL vs. SingleStore vs. TimesTen vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

Relational DBMS

using the Octo plugin

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

Score	6.85
Rank	#51	Overall
	#30	Relational DBMS

Score	0.41
Rank	#261	Overall
	#122	Relational DBMS

Score	4.22
Rank	#69	Overall
	#37	Relational DBMS

Score	1.23
Rank	#163	Overall
	#74	Relational DBMS

Score	0.20
Rank	#308	Overall
	#43	Key-value stores

Website

greenplum.org

www.postgres-xl.org

www.singlestore.com

www.oracle.com/database/technologies/related/timesten.html

yottadb.com

Technical documentation

docs.greenplum.org

www.postgres-xl.org/documentation

docs.singlestore.com

docs.oracle.com/en/database/other-databases/timesten/index.html

yottadb.com/resources/documentation

Developer

Pivotal Software Inc.

SingleStore Inc.

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

YottaDB, LLC

Initial release

2005

2014

since 2012, originally named StormDB

2013

1998

2001

Current release

7.0.0, September 2023

10 R1, October 2018

8.5, January 2024

Release 22.1

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Mozilla public license

commercial

free developer edition available

commercial

Open Source

AGPL 3.0

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++, Go

Server operating systems

Linux

Linux
macOS

Linux

64 bit version required

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Docker
Linux

Data scheme

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

since Version 4.2

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

but no triggers and foreign keys

yes

by using the Octo plugin

APIs and other access methods

JDBC
ODBC

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

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C
Java
Perl
Python
R

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

Bash
C
C#
Java
JavaScript (Node.js)
Python

C
C++
Java
Node.js
PL/SQL
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

hash partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

yes

by means of logfiles and checkpoints

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

Fine grained access control via users, groups and roles

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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More resources

DB-Engines blog posts

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SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022, Akmal Chaudhri, SingleStore (sponsor)

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