DBMS > Citus vs. Hazelcast vs. Microsoft Access vs. MySQL vs. OpenTSDB

System Properties Comparison Citus vs. Hazelcast vs. Microsoft Access vs. MySQL vs. OpenTSDB

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A widely adopted in-memory data grid

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

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Website

www.citusdata.com

hazelcast.com

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

www.mysql.com

opentsdb.net

Technical documentation

docs.citusdata.com

hazelcast.org/imdg/docs

developer.microsoft.com/en-us/access

dev.mysql.com/doc

opentsdb.net/docs/build/html/index.html

Developer

Hazelcast

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

currently maintained by Yahoo and other contributors

Initial release

2010

2008

1992

1995

2011

Current release

8.1, December 2018

5.3.6, November 2023

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2; commercial licenses available

commercial

Bundled with Microsoft Office

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

LGPL

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

C and C++

Java

Server operating systems

Linux

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

specific XML type available, but no XML query functionality

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like query language

yes

but not compliant to any SQL standard

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Telnet API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Event Listeners, Executor Services

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Triggers

yes

Events

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

Replicated Map

none

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

but no files for transaction logging

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

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

Role-based access control

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

Users with fine-grained authorization concept

no user groups or roles

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