DBMS > AgensGraph vs. Heroic vs. MonetDB vs. Yaacomo

System Properties Comparison AgensGraph vs. Heroic vs. MonetDB 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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A relational database management system that stores data in columns

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

Primary database model

Graph DBMS
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Website

bitnine.net/agensgraph

github.com/spotify/heroic

www.monetdb.org

yaacomo.com

Technical documentation

bitnine.net/documentation

spotify.github.io/heroic

www.monetdb.org/Documentation

Developer

Bitnine Global Inc.

Spotify

MonetDB BV

Q2WEB GmbH

Initial release

2016

2014

2004

2009

Current release

2.1, December 2018

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Mozilla Public License 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

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Android
Linux
Windows

Data scheme

depending on used data model

schema-free

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

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

APIs and other access methods

Cypher Query Language
JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

yes

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Sharding via remote tables

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

Source-replica replication available in experimental status

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate 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

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

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More resources

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