DBMS > EsgynDB vs. Greenplum vs. Hypertable vs. XTDB

System Properties Comparison EsgynDB vs. Greenplum vs. Hypertable vs. XTDB

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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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Wide column store

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.esgyn.cn

greenplum.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.greenplum.org

www.xtdb.com/docs

Developer

Esgyn

Pivotal Software Inc.

Hypertable Inc.

Juxt Ltd.

Initial release

2015

2005

2009

2019

Current release

7.0.0, September 2023

0.9.8.11, March 2016

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

Open Source

MIT 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++, Java

C++

Clojure

Server operating systems

Linux

Linux
OS X
Windows

an inofficial Windows port is available

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL

Support of SQL

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

C++ API
Thrift

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
Java
Perl
Python
R

C++
Java
Perl
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

selectable replication factor on file system level

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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