DBMS > AnzoGraph DB vs. ClickHouse vs. Derby vs. HBase vs. mSQL

System Properties Comparison AnzoGraph DB vs. ClickHouse vs. Derby vs. HBase vs. mSQL

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

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Secondary database models

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	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Website

cambridgesemantics.com/anzograph

clickhouse.com

db.apache.org/derby

hbase.apache.org

hughestech.com.au/products/msql

Technical documentation

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

clickhouse.com/docs

db.apache.org/derby/manuals/index.html

hbase.apache.org/book.html

Developer

Cambridge Semantics

Clickhouse Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Hughes Technologies

Initial release

2018

2016

1997

2008

1994

Current release

2.3, January 2021

v24.4.1.2088-stable, May 2024

10.17.1.0, November 2023

2.3.4, January 2021

4.4, October 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

Apache version 2

commercial

free licenses can be provided

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.

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
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Implementation language

C++

Java

Server operating systems

Linux

FreeBSD
Linux
macOS

All OS with a Java VM

Linux
Unix
Windows

using Cygwin

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

Close to ANSI SQL (SQL/JSON + extensions)

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

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

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC

Java API
RESTful HTTP API
Thrift

JDBC
ODBC

Supported programming languages

C++
Java
Python

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Java Stored Procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

key based and custom

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Source-replica replication

Multi-source replication
Source-replica replication

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

Immediate Consistency or Eventual Consistency

none

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

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

Access rights for users and roles

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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