DBMS > Atos Standard Common Repository vs. etcd vs. SiteWhere vs. SQLite vs. Teradata Aster

System Properties Comparison Atos Standard Common Repository vs. etcd vs. SiteWhere vs. SQLite vs. Teradata Aster

Editorial information provided by DB-Engines

Name

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

Teradata Aster has been integrated into other Teradata systems and therefore 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 distributed reliable key-value store

M2M integration platform for persisting/querying time series data

Widely used embeddable, in-process RDBMS

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Key-value store

Key-value store

Time Series DBMS

Relational DBMS

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

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

etcd.io
github.com/etcd-io/etcd

github.com/sitewhere/sitewhere

www.sqlite.org

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

sitewhere1.sitewhere.io/index.html

www.sqlite.org/docs.html

Developer

Atos Convergence Creators

SiteWhere

Dwayne Richard Hipp

Teradata

Initial release

2016

2010

2000

2005

Current release

1703

3.4, August 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Common Public Attribution License Version 1.0

Open Source

Public Domain

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

Linux
OS X
Windows

server-less

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

predefined scheme

yes

dynamic column types

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

optional

yes

not rigid because of 'dynamic typing' concept.

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

APIs and other access methods

LDAP

gRPC
JSON over HTTP

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

R packages

Triggers

yes

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on HBase

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor

based on HBase

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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