DBMS > 4D vs. Atos Standard Common Repository vs. KeyDB vs. SiteWhere vs. Teradata Aster

System Properties Comparison 4D vs. Atos Standard Common Repository vs. KeyDB vs. SiteWhere 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

Application development environment with integrated database management system

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

M2M integration platform for persisting/querying time series data

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

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	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

www.4d.com

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

github.com/Snapchat/KeyDB
keydb.dev

github.com/sitewhere/sitewhere

Technical documentation

developer.4d.com

docs.keydb.dev

sitewhere1.sitewhere.io/index.html

Developer

4D, Inc

Atos Convergence Creators

EQ Alpha Technology Ltd.

SiteWhere

Teradata

Initial release

1984

2016

2019

2010

2005

Current release

v20, April 2023

1703

License

Commercial or Open Source

commercial

Open Source

BSD-3

Open Source

Common Public Attribution License Version 1.0

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

C++

Java

Server operating systems

OS X
Windows

Linux

Linux
OS X
Windows

Linux

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

predefined scheme

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

yes

optional

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

Proprietary protocol

RESP - REdis Serialization Protoco

HTTP REST

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

Lua

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

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

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Strong eventual consistency with CRDTs

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

ACID

Atomic execution of specific operations

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Users and groups

LDAP bind authentication

simple password-based access control and ACL

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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