DBMS > Google BigQuery vs. KairosDB vs. MySQL vs. SAP HANA vs. SiriDB

System Properties Comparison Google BigQuery vs. KairosDB vs. MySQL vs. SAP HANA vs. SiriDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Distributed Time Series DBMS based on Cassandra or H2

Widely used open source RDBMS

In-memory, column based data store. Available as appliance or cloud service

Open Source Time Series DBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

cloud.google.com/bigquery

github.com/kairosdb/kairosdb

www.mysql.com

www.sap.com/products/hana.html

siridb.com

Technical documentation

cloud.google.com/bigquery/docs

Developer

Google

Oracle

since 2010, originally MySQL AB, then Sun

SAP

Cesbit

Initial release

2010

2013

1995

2010

2017

Current release

1.2.2, November 2018

8.4.0, April 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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Implementation language

Java

C and C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

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

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

RESTful HTTP/JSON API

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
JavaScript

Node.js
PHP
Python

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

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

proprietary syntax

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

not for MyISAM storage engine

ACID

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

simple password-based access control

Users with fine-grained authorization concept

no user groups or roles

yes

simple rights management via user accounts

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