DBMS > Datastax Enterprise vs. GBase vs. IBM Db2 Event Store

System Properties Comparison Datastax Enterprise vs. GBase vs. IBM Db2 Event Store

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Wide column store

Relational DBMS

Event Store
Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	3.94
Rank	#67	Overall
	#4	Wide column stores

Score	1.49
Rank	#142	Overall
	#64	Relational DBMS

Score	0.18
Rank	#312	Overall
	#2	Event Stores
	#26	Time Series DBMS

Website

www.datastax.com/products/datastax-enterprise

www.gbase.cn

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

Technical documentation

docs.datastax.com

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

Developer

DataStax

General Data Technology Co., Ltd.

IBM

Initial release

2011

2004

2017

Current release

6.8, April 2020

GBase 8a, GBase 8s, GBase 8c

2.0

License

Commercial or Open Source

commercial

free developer edition available

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

Java

C, Java, Python

C and C++

Server operating systems

Linux
OS X

Linux

Linux, macOS, Windows for the developer addition

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

Standard with numerous extensions

yes

through the embedded Spark runtime

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

ADO.NET
C API
JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

yes

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

Durability

Support for making data persistent

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users can be defined per object

yes

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

IBM to acquire DataStax, helping clients bring the power of unstructured data to enterprise AI applications
25 February 2025, IBM

Big Blue To Acquire Datastax in Enterprise AI Play
28 February 2025, Redmond Channel Partner

IBM to Acquire DataStax, Deepening watsonx Capabilities and Addressing Generative AI Data Needs for the Enterprise
25 February 2025, PR Newswire

Langflow by DataStax is hands down the best for multi-agent systems.
5 April 2025, Amazon Web Services (AWS)

IBM to Acquire DataStax to Power Generative AI, Tapping into 93% of Enterprise Data
26 February 2025, eWEEK

provided by Google News

Share this page