DBMS > AnzoGraph DB vs. H2 vs. HyperSQL vs. Microsoft Azure AI Search vs. RavenDB

System Properties Comparison AnzoGraph DB vs. H2 vs. HyperSQL vs. Microsoft Azure AI Search vs. RavenDB

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Search-as-a-service for web and mobile app development

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Secondary database models

Spatial DBMS

Vector DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

cambridgesemantics.com/anzograph

www.h2database.com

hsqldb.org

azure.microsoft.com/en-us/services/search

ravendb.net

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

www.h2database.com/html/main.html

hsqldb.org/web/hsqlDocsFrame.html

learn.microsoft.com/en-us/azure/search

ravendb.net/docs

Developer

Cambridge Semantics

Thomas Mueller

Microsoft

Hibernating Rhinos

Initial release

2018

2005

2001

2015

2010

Current release

2.3, January 2021

2.2.220, July 2023

2.7.2, June 2023

5.4, July 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

based on BSD license

commercial

Open Source

AGPL version 3, commercial license available

Cloud-based only

Only available as a cloud service

yes

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

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

Linux
macOS
Raspberry Pi
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

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

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

SQL-like query language (RQL)

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

C++
Java
Python

Java

All languages supporting JDBC/ODBC
Java

C#
Java
JavaScript
Python

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures and User-Defined Functions

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

With clustering: 2 database servers on different computers operate on identical copies of a database

none

yes

Implicit feature of the cloud service

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (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

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

yes

using Azure authentication

Authorization levels configured per client per database

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More resources

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