DBMS > CrateDB vs. Greenplum vs. JaguarDB vs. MaxDB vs. TimescaleDB

System Properties Comparison CrateDB vs. Greenplum vs. JaguarDB vs. MaxDB vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

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.

Performant, highly scalable DBMS for AI and IoT applications

A robust and reliable RDBMS optimized to run all major SAP solutions

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	2.15
Rank	#115	Overall
	#55	Relational DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Website

Technical documentation

cratedb.com/docs

docs.greenplum.org

www.jaguardb.com/support.html

maxdb.sap.com/documentation

docs.timescale.com

Developer

Crate

Pivotal Software Inc.

DataJaguar, Inc.

SAP, acquired from Software AG (Adabas-D) in 1997

Timescale

Initial release

2013

2005

2015

1984

2017

Current release

5.8.1, August 2024

7.0.0, September 2023

3.3 July 2023

7.9.10.12, February 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL V3.0

commercial

Limited community edition free

Open Source

Apache 2.0

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

Java

C++

the server part. Clients available in other languages

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

full PostgreSQL SQL syntax

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

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

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C
Java
Perl
Python
R

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

.Net
C#
Java
Perl
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Source-replica replication

Multi-source replication

Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

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.

User concepts

Access control

rights management via user accounts

fine grained access rights according to SQL-standard

rights management via user accounts

fine grained access rights according to SQL-standard

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More resources

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