DBMS > AgensGraph vs. Couchbase vs. HEAVY.AI vs. Ingres vs. InterSystems IRIS

System Properties Comparison AgensGraph vs. Couchbase vs. HEAVY.AI vs. Ingres vs. InterSystems IRIS

Editorial information provided by DB-Engines

Name

Description

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Well established RDBMS

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

Primary database model

Graph DBMS
Relational DBMS

Document store

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial 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	17.30
Rank	#36	Overall
	#5	Document stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	4.05
Rank	#83	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Website

bitnine.net/agensgraph

www.couchbase.com

github.com/heavyai/heavydb
www.heavy.ai

www.actian.com/databases/ingres

www.intersystems.com/products/intersystems-iris

Technical documentation

bitnine.net/documentation

docs.couchbase.com

docs.heavy.ai

docs.actian.com/ingres

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

Developer

Bitnine Global Inc.

Couchbase, Inc.

HEAVY.AI, Inc.

Actian Corporation

InterSystems

Initial release

2016

2011

2016

1974

originally developed at University Berkely in early 1970s

2018

Current release

2.1, December 2018

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

5.10, January 2022

11.2, May 2022

2023.3, June 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2; enterprise edition available

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

C, C++, Go and Erlang

C++ and CUDA

Server operating systems

Linux
OS X
Windows

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

AIX
Linux
macOS
Ubuntu
Windows

Data scheme

depending on used data model

schema-free

yes

depending on used data model

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

APIs and other access methods

Cypher Query Language
JDBC

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JDBC
ODBC
Thrift
Vega

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Automatic Sharding

Sharding

Round robin

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication

Ingres Replicator

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
Immediate Consistency

selectable on a per-operation basis

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

MVCC

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

Ephemeral buckets

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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