DBMS > Atos Standard Common Repository vs. etcd vs. SQLite vs. TerminusDB vs. Transwarp Hippo

System Properties Comparison Atos Standard Common Repository vs. etcd vs. SQLite vs. TerminusDB vs. Transwarp Hippo

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 distributed reliable key-value store

Widely used embeddable, in-process RDBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Document store
Key-value store

Secondary database models

Document store
RDF store

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Website

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

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

www.sqlite.org

terminusdb.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

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

www.sqlite.org/docs.html

terminusdb.github.io/terminusdb/#

Developer

Atos Convergence Creators

Dwayne Richard Hipp

DataChemist Ltd.

Initial release

2016

2000

2018

2023

Current release

1703

3.4, August 2019

3.46.0 (23 May 2024), May 2024

11.0.0, January 2023

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Public Domain

Open Source

GPL V3

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

Prolog, Rust

C++

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

server-less

Linux

Linux
macOS

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

optional

yes

not rigid because of 'dynamic typing' concept.

yes

Vector, Numeric and String

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

SQL-92 is not fully supported

SQL-like query language (WOQL)

APIs and other access methods

LDAP

gRPC
JSON over HTTP

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

RESTful HTTP API

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

JavaScript
Python

C++
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Graph Partitioning

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.

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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 journaling

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

Role-based access control

Role based access control and fine grained access rights

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