DBMS > KairosDB vs. Kinetica vs. Microsoft Access vs. Percona Server for MySQL vs. Snowflake

System Properties Comparison KairosDB vs. Kinetica vs. Microsoft Access vs. Percona Server for MySQL vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Distributed Time Series DBMS based on Cassandra or H2

Fully vectorized database across both GPUs and CPUs

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.)

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

github.com/kairosdb/kairosdb

www.kinetica.com

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

www.percona.com/software/mysql-database/percona-server

www.snowflake.com

Technical documentation

kairosdb.github.io

docs.kinetica.com

developer.microsoft.com/en-us/access

www.percona.com/downloads/Percona-Server-LATEST

docs.snowflake.net/manuals/index.html

Developer

Kinetica

Microsoft

Percona

Snowflake Computing Inc.

Initial release

2013

2012

1992

2008

2014

Current release

1.2.2, November 2018

7.1, August 2021

1902 (16.0.11328.20222), March 2019

8.0.36-28, 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

C++

C and C++

Server operating systems

Linux
OS X
Windows

Linux

Windows

Not a real database server, but making use of DLLs

Linux

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

but not compliant to any SQL standard

yes

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

C++
Java
JavaScript (Node.js)
Python

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

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

since Access 2010 using the ACE-engine

yes

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

since Access 2010 using the ACE-engine

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

none

Multi-source replication
Source-replica replication
XtraDB Cluster

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

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

GPU vRAM or System RAM

yes

User concepts

Access control

simple password-based access control

Access rights for users and roles on table level

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

Users with fine-grained authorization concept

no user groups or roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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