DBMS > IBM Db2 Event Store vs. Microsoft Access vs. MySQL vs. Riak TS vs. SiriDB

System Properties Comparison IBM Db2 Event Store vs. Microsoft Access vs. MySQL vs. Riak TS vs. SiriDB

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used open source RDBMS

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Open Source Time Series DBMS

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Document store
Spatial 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	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

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

www.microsoft.com/en-us/microsoft-365/access

www.mysql.com

siridb.com

Technical documentation

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

developer.microsoft.com/en-us/access

dev.mysql.com/doc

www.tiot.jp/riak-docs/riak/ts/latest

docs.siridb.com

Developer

IBM

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Open Source, formerly Basho Technologies

Cesbit

Initial release

2017

1992

1995

2015

2017

Current release

2.0

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

3.0.0, September 2022

License

Commercial or Open Source

commercial

free developer edition available

commercial

Bundled with Microsoft Office

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

C++

C and C++

Erlang

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

restricted

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

but not compliant to any SQL standard

yes

with proprietary extensions

yes, limited

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Native Erlang Interface

HTTP API

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++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Erlang

Triggers

yes

since Access 2010 using the ACE-engine

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

Multi-source replication
Source-replica replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

links between datasets can be stored

Transaction concepts

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

ACID

but no files for transaction logging

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

table locks or row locks depending on storage engine

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

but no files for transaction logging

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

fine grained access rights according to SQL-standard

a simple user-level security was built in till version Access 2003

Users with fine-grained authorization concept

no user groups or roles

simple rights management via user accounts

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