DBMS > Greenplum vs. Infobright vs. RavenDB vs. Tkrzw

System Properties Comparison Greenplum vs. Infobright vs. RavenDB vs. Tkrzw

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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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Open Source Operational and Transactional Enterprise NoSQL Document Database

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Document store

Key-value store

Secondary database models

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

greenplum.org

ignitetech.com/softwarelibrary/infobrightdb

ravendb.net

dbmx.net/tkrzw

Technical documentation

docs.greenplum.org

ravendb.net/docs

Developer

Pivotal Software Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Hibernating Rhinos

Mikio Hirabayashi

Initial release

2005

2010

2020

Current release

7.0.0, September 2023

5.4, July 2022

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

AGPL version 3, commercial license available

Open Source

Apache Version 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

C++

Server operating systems

Linux

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
macOS

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

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Authorization levels configured per client per database

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More resources

Recent citations in the news

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
6 December 2018, O'Reilly Media

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services
9 September 2019, AWS Blog

RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

Greenplum 6 ventures outside the analytic box | ZDNET
19 March 2019, ZDNet

Greenplum 6 review: Jack of all trades, master of some
7 November 2019, InfoWorld

provided by Google News

RavenDB Launches Version 6.0 Lightning Fast Queries, Data Integrations, Corax Indexing Engine, and Sharding
3 October 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

RavenDB Adds Graph Queries
15 May 2019, Datanami

Review: NoSQL database RavenDB
20 March 2019, TechGenix

How I Created a RavenDB Python Client
23 September 2016, Visual Studio Magazine

provided by Google News

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