DBMS > AgensGraph vs. Apache Phoenix vs. Graph Engine vs. Yaacomo

System Properties Comparison AgensGraph vs. Apache Phoenix vs. Graph Engine vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Website

bitnine.net/agensgraph

phoenix.apache.org

www.graphengine.io

yaacomo.com

Technical documentation

bitnine.net/documentation

phoenix.apache.org

www.graphengine.io/docs/manual

Developer

Bitnine Global Inc.

Apache Software Foundation

Microsoft

Q2WEB GmbH

Initial release

2016

2014

2010

2009

Current release

2.1, December 2018

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

Open Source

MIT License

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

.NET and C

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

.NET

Android
Linux
Windows

Data scheme

depending on used data model

yes

late-bound, schema-on-read capabilities

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Cypher Query Language
JDBC

JDBC

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C#
C++
F#
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

fine grained access rights according to SQL-standard

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