DBMS > GeoMesa vs. IBM Db2 Event Store vs. SAP IQ vs. XTDB

System Properties Comparison GeoMesa vs. IBM Db2 Event Store vs. SAP IQ vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Distributed Event Store optimized for Internet of Things use cases

Columnar RDBMS optimized for Big Data analytics

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

Primary database model

Spatial DBMS

Event Store
Time Series DBMS

Relational DBMS

column-oriented

Document store

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

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

www.geomesa.org

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

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

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

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

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

help.sap.com/docs/SAP_IQ

www.xtdb.com/docs

Developer

CCRi and others

IBM

SAP, formerly Sybase

Juxt Ltd.

Initial release

2014

2017

1994

2019

Current release

4.0.5, February 2024

2.0

16.1 SPS04, April 2019

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free developer edition available

commercial

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

Scala

C and C++

Clojure

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
Solaris
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Active-active shard replication

SAP/Sybase Replication Server

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Eventual Consistency

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

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

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

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

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Capture and Analyze XXL Data Streams with IBM Db2 Event Store 2.0
22 August 2019, ibm.com

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

Best cloud databases of 2022
4 October 2022, ITPro

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

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

provided by Google News

New Services in SAP HANA Cloud Lower TCO for Customers in Data-Intensive, Highly Regulated Industries
7 April 2021, SAP News

SAP Products & Services Data Portfolio
2 July 2021, Datamation

Independent Research Firm Names SAP a Leader in Data Management for Analytics
17 February 2020, SAP News

SAP Scales Out HANA In-Memory For Clouds
6 March 2014, EnterpriseAI

Rolta Receives 2014 SAP® Pinnacle Award: OEM Partner of the Year
22 April 2014, PR Newswire

provided by Google News

Share this page