DBMS > Atos Standard Common Repository vs. Drizzle vs. FoundationDB vs. HugeGraph vs. TigerGraph

System Properties Comparison Atos Standard Common Repository vs. Drizzle vs. FoundationDB vs. HugeGraph vs. TigerGraph

Editorial information provided by DB-Engines

Name

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

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Ordered key-value store. Core features are complimented by layers.

A fast-speed and highly-scalable Graph DBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store
Key-value store

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Graph DBMS

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

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

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

github.com/apple/foundationdb

github.com/hugegraph
hugegraph.apache.org

www.tigergraph.com

Technical documentation

apple.github.io/foundationdb

hugegraph.apache.org/docs

docs.tigergraph.com

Developer

Atos Convergence Creators

Drizzle project, originally started by Brian Aker

FoundationDB

Baidu

Initial release

2016

2008

2013

2018

2017

Current release

1703

7.2.4, September 2012

6.2.28, November 2020

0.9

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
OS X
Windows

Linux
macOS
Unix

Linux

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

optional

yes

some layers support typing

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

Secondary indexes

yes

also supports composite index and range index

SQL

Support of SQL

yes

with proprietary extensions

supported in specific SQL layer only

SQL-like query language (GSQL)

APIs and other access methods

LDAP

JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

All languages with LDAP bindings

C
C++
Java
PHP

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Groovy
Java
Python

C++
Java

Server-side scripts

Stored procedures

in SQL-layer only

asynchronous Gremlin script jobs

yes

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Linearizable consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

in SQL-layer only

yes

edges in graph

yes

Relationships in graphs

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users, roles and permissions

Role-based access control

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More resources

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