DBMS > EsgynDB vs. HBase vs. MonetDB vs. RocksDB

System Properties Comparison EsgynDB vs. HBase vs. MonetDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

A relational database management system that stores data in columns

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	1.72
Rank	#148	Overall
	#68	Relational DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

Technical documentation

hbase.apache.org/book.html

www.monetdb.org/Documentation

github.com/facebook/rocksdb/wiki

Developer

Esgyn

Apache Software Foundation

Apache top-level project, originally developed by Powerset

MonetDB BV

Facebook, Inc.

Initial release

2015

2008

2004

2013

Current release

2.3.4, January 2021

Dec2023 (11.49), December 2023

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Mozilla Public License 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Java

C++

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

Java API
RESTful HTTP API
Thrift

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Coprocessors in Java

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Multi-source replication
Source-replica replication

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

yes

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

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

fine grained access rights according to SQL-standard

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