DBMS > AgensGraph vs. Graph Engine vs. Hypertable vs. Sequoiadb

System Properties Comparison AgensGraph vs. Graph Engine vs. Hypertable vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

An open source BigTable implementation based on distributed file systems such as Hadoop

NewSQL database with distributed OLTP and SQL

Primary database model

Graph DBMS
Relational DBMS

Graph DBMS
Key-value store

Wide column store

Document store
Relational DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

bitnine.net/agensgraph

www.graphengine.io

www.sequoiadb.com

Technical documentation

bitnine.net/documentation

www.graphengine.io/docs/manual

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Bitnine Global Inc.

Microsoft

Hypertable Inc.

Sequoiadb Ltd.

Initial release

2016

2010

2009

2013

Current release

2.1, December 2018

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

MIT License

Open Source

GNU version 3. Commercial license available

Open Source

Server: AGPL; Client: Apache V2

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

.NET and C

C++

Server operating systems

Linux
OS X
Windows

.NET

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Cypher Query Language
JDBC

RESTful HTTP API

C++ API
Thrift

proprietary protocol using JSON

Supported programming languages

C
Java
JavaScript
Python

C#
C++
F#
Visual Basic

C++
Java
Perl
PHP
Python
Ruby

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor on file system level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

fine grained access rights according to SQL-standard

simple password-based access control

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