DBMS > Atos Standard Common Repository vs. Google Cloud Spanner vs. KairosDB vs. MySQL vs. OpenTSDB

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Spanner vs. KairosDB vs. MySQL vs. OpenTSDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Distributed Time Series DBMS based on Cassandra or H2

Widely used open source RDBMS

Scalable Time Series DBMS based on HBase

Primary database model

Document store
Key-value store

Relational DBMS

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	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

cloud.google.com/spanner

github.com/kairosdb/kairosdb

www.mysql.com

opentsdb.net

Technical documentation

cloud.google.com/spanner/docs

kairosdb.github.io

dev.mysql.com/doc

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

Developer

Atos Convergence Creators

Google

Oracle

since 2010, originally MySQL AB, then Sun

currently maintained by Yahoo and other contributors

Initial release

2016

2017

2013

1995

2011

Current release

1703

1.2.2, November 2018

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

LGPL

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java

C and C++

Java

Server operating systems

Linux

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

optional

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

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

with proprietary extensions

APIs and other access methods

LDAP

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Telnet API

Supported programming languages

All languages with LDAP bindings

Go
Java
JavaScript (Node.js)
Python

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on Cassandra

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic execution of specific operations

ACID

Strict serializable isolation

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

In-memory capabilities

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

yes

User concepts

Access control

LDAP bind authentication

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

simple password-based access control

Users with fine-grained authorization concept

no user groups or roles

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