DBMS > GBase vs. IBM Db2 Event Store vs. Percona Server for MongoDB vs. Postgres-XL

System Properties Comparison GBase vs. IBM Db2 Event Store vs. Percona Server for MongoDB vs. Postgres-XL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An analytical database for business intelligence with large customers in China.

Distributed Event Store optimized for Internet of Things use cases

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

www.gbase.cn

www.ibm.com/products/db2-event-store

www.percona.com/mongodb/software/percona-server-for-mongodb

www.postgres-xl.org

Technical documentation

www.ibm.com/docs/en/db2-event-store

docs.percona.com/percona-distribution-for-mongodb

www.postgres-xl.org/documentation

Developer

IBM

Percona

Initial release

2017

2015

2014

since 2012, originally named StormDB

Current release

GBase 8a

2.0

3.4.10-2.10, November 2017

10 R1, October 2018

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL Version 2

Open Source

Mozilla public 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 and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux

Linux
macOS

Data scheme

yes

schema-free

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

distributed, parallel query execution

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

proprietary protocol using JSON

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard 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

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

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

yes

via In-Memory Engine

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

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

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, ibm.com

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

provided by Google News

5 Reasons to Run MongoDB on Kubernetes
6 March 2024, The New Stack

A New Way to Provision Databases on Kubernetes
21 March 2024, hackernoon.com

FerretDB goes GA: Gives you MongoDB, without the MongoDB...
15 May 2023, The Stack

Unlock MongoDB's Full Potential: Ensuring Post-Upgrade Success
22 February 2024, The New Stack

Percona launches management system aimed at open-source databases
17 May 2022, The Register

provided by Google News

Share this page