DBMS > AnzoGraph DB vs. Google Cloud Bigtable vs. H2 vs. HyperSQL

System Properties Comparison AnzoGraph DB vs. Google Cloud Bigtable vs. H2 vs. HyperSQL

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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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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

Primary database model

Graph DBMS
RDF store

Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	3.90
Rank	#85	Overall
	#46	Relational DBMS

Website

cambridgesemantics.com/anzograph

cloud.google.com/bigtable

www.h2database.com

hsqldb.org

Technical documentation

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

cloud.google.com/bigtable/docs

www.h2database.com/html/main.html

hsqldb.org/web/hsqlDocsFrame.html

Developer

Cambridge Semantics

Google

Thomas Mueller

Initial release

2018

2015

2005

2001

Current release

2.3, January 2021

2.2.220, July 2023

2.7.2, June 2023

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

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

Open Source

based on BSD license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux

hosted

All OS with a Java VM

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

Data scheme

Schema-free and OWL/RDFS-schema support

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

SQL

Support of SQL

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

yes

APIs and other access methods

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

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

C++
Java
Python

C#
C++
Go
Java
JavaScript (Node.js)
Python

Java

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures and User-Defined Functions

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Internal replication in Colossus, and regional replication between two clusters in different zones

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

none

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 (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

How Knowledge Graphs Automate Data Preparation
15 July 2020, Database Trends and Applications

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