DBMS > Greenplum vs. Hypertable vs. KeyDB

System Properties Comparison Greenplum vs. Hypertable vs. KeyDB

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

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.

An open source BigTable implementation based on distributed file systems such as Hadoop

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Primary database model

Relational DBMS

Wide column store

Key-value store

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	0.80
Rank	#219	Overall
	#31	Key-value stores

Website

greenplum.org

github.com/Snapchat/KeyDB
keydb.dev

Technical documentation

docs.greenplum.org

docs.keydb.dev

Developer

Pivotal Software Inc.

Hypertable Inc.

EQ Alpha Technology Ltd.

Initial release

2005

2009

2019

Current release

7.0.0, September 2023

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

Open Source

BSD-3

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
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

restricted

only exact value or prefix value scans

yes

by using the Redis Search module

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

C++ API
Thrift

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

C
Java
Perl
Python
R

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor on file system level

Multi-source replication
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
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple password-based access control and ACL

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More resources

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