DBMS > Greenplum vs. LevelDB vs. Sequoiadb vs. Transbase

System Properties Comparison Greenplum vs. LevelDB vs. Sequoiadb vs. Transbase

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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.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

NewSQL database with distributed OLTP and SQL

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key-value store

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	9.23
Rank	#47	Overall
	#30	Relational DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	0.48
Rank	#260	Overall
	#41	Document stores
	#121	Relational DBMS

Score	0.15
Rank	#337	Overall
	#147	Relational DBMS

Website

greenplum.org

github.com/google/leveldb

www.sequoiadb.com

www.transaction.de/en/products/transbase.html

Technical documentation

docs.greenplum.org

github.com/google/leveldb/blob/main/doc/index.md

www.sequoiadb.com/en/index.php?m=Files&a=index

www.transaction.de/en/products/transbase/features.html

Developer

Pivotal Software Inc.

Google

Sequoiadb Ltd.

Transaction Software GmbH

Initial release

2005

2011

2013

1987

Current release

7.0.0, September 2023

1.23, February 2021

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

Server: AGPL; Client: Apache V2

commercial

free development license

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++

C and C++

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

proprietary protocol using JSON

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
Java
Perl
Python
R

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C++
Java
PHP
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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