DBMS > EsgynDB vs. Greenplum vs. IBM Db2 warehouse vs. TerarkDB vs. Warp 10

System Properties Comparison EsgynDB vs. Greenplum vs. IBM Db2 warehouse vs. TerarkDB vs. Warp 10

Editorial information provided by DB-Engines

Name

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.

Cloud-based data warehousing service

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

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	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.esgyn.cn

greenplum.org

www.ibm.com/products/db2/warehouse

github.com/bytedance/terarkdb

www.warp10.io

Technical documentation

docs.greenplum.org

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

www.warp10.io/content/02_Getting_started

Developer

Esgyn

Pivotal Software Inc.

IBM

ByteDance, originally Terark

SenX

Initial release

2015

2005

2014

2016

2015

Current release

7.0.0, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted open source version available

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

C++

Java

Server operating systems

Linux

hosted

Linux
OS X
Windows

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

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

.NET Client API
JDBC
ODBC
OLE DB

C++ API
Java API

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
Java
Perl
Python
R

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

PL/SQL, SQL PL

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

yes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

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

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

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

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

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

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

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

provided by Google News

Introducing the next generation of Db2 Warehouse: Our cost-effective, cloud-native data warehouse built for always-on ...
11 July 2023, IBM

Db2 Warehouse delivers 4x faster query performance than previously, while cutting storage costs by 34x
11 July 2023, IBM

Top 7 Cloud Data Warehouse Companies
31 May 2023, Datamation

Announcing the availability of Bring-Your-Own-License and Reserved Instance plans for next generation Db2 ...
7 August 2023, IBM

Data mining in Db2 Warehouse: the basics
23 June 2020, Towards Data Science

provided by Google News

Time Series Databases Software Market [2024-2031] | InfluxData, Trendalyze, Amazon Timestream
11 May 2024, Motions Online

Time Series Intelligence Software Market Business Insights, Key Trend Analysis | Google, SAP, Azure Time Series ...
24 April 2024, Amoré

Time Series Intelligence Software Market Analysis and Revenue Prediction | Azure Time Series Insights, Trendalyze ...
20 May 2024, Weekly Post Gazette

provided by Google News

Share this page