DBMS > Galaxybase vs. IBM Db2 Event Store vs. KairosDB vs. SAP HANA

System Properties Comparison Galaxybase vs. IBM Db2 Event Store vs. KairosDB vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

Distributed Event Store optimized for Internet of Things use cases

Distributed Time Series DBMS based on Cassandra or H2

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Graph DBMS

Event Store
Time Series DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

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

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

galaxybase.com

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

github.com/kairosdb/kairosdb

www.sap.com/products/hana.html

Technical documentation

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

kairosdb.github.io

help.sap.com/hana

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

IBM

SAP

Initial release

2017

2013

2010

Current release

Nov 20, November 2021

2.0

1.2.2, November 2018

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and Java

C and C++

Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

Appliance or cloud-service

Data scheme

Strong typed schema

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC

Supported programming languages

Go
Java
Python

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

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined procedures and functions

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

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

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

Role-based access control

fine grained access rights according to SQL-standard

simple password-based access control

yes

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