DBMS > IBM Db2 Event Store vs. mSQL vs. OrigoDB vs. SpatiaLite vs. XTDB

System Properties Comparison IBM Db2 Event Store vs. mSQL vs. OrigoDB vs. SpatiaLite vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

Spatial extension of SQLite

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

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Spatial DBMS

Document store

Secondary database models

Relational DBMS

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

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

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

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

hughestech.com.au/products/msql

origodb.com

www.gaia-gis.it/fossil/libspatialite/index

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

Technical documentation

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

origodb.com/docs

www.gaia-gis.it/gaia-sins/spatialite_topics.html

www.xtdb.com/docs

Developer

IBM

Hughes Technologies

Robert Friberg et al

Alessandro Furieri

Juxt Ltd.

Initial release

2017

1994

2009

under the name LiveDB

2008

2019

Current release

2.0

4.4, October 2021

5.0.0, August 2020

1.19, September 2021

License

Commercial or Open Source

commercial

free developer edition available

commercial

free licenses can be provided

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

C and C++

C++

Clojure

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

server-less

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

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

.NET Client API
HTTP API
LINQ

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++
Delphi
Java
Perl
PHP
Tcl

.Net

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

Source-replica replication

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

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

Write ahead log

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role based authorization

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