DBMS > IBM Db2 Event Store vs. Linter vs. mSQL vs. XTDB

System Properties Comparison IBM Db2 Event Store vs. Linter vs. mSQL vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

RDBMS for high security requirements

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

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

linter.ru

hughestech.com.au/products/msql

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

Technical documentation

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

www.xtdb.com/docs

Developer

IBM

relex.ru

Hughes Technologies

Juxt Ltd.

Initial release

2017

1990

1994

2019

Current release

2.0

4.4, October 2021

1.19, September 2021

License

Commercial or Open Source

commercial

free developer edition available

commercial

free licenses can be provided

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++

Clojure

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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

A subset of ANSI SQL is implemented

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

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
ODBC

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
Qt
Ruby
Tcl

C
C++
Delphi
Java
Perl
PHP
Tcl

Clojure
Java

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

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

Immediate Consistency

none

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

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

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

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