DBMS > Ehcache vs. InfinityDB vs. MonetDB vs. SQL.JS vs. TerarkDB

System Properties Comparison Ehcache vs. InfinityDB vs. MonetDB vs. SQL.JS vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

A Java embedded Key-Value Store which extends the Java Map interface

A relational database management system that stores data in columns

Port of SQLite to JavaScript

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Key-value store

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

github.com/bytedance/terarkdb

Technical documentation

www.ehcache.org/documentation

boilerbay.com/infinitydb/manual

www.monetdb.org/Documentation

sql.js.org/documentation/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Terracotta Inc, owned by Software AG

Boiler Bay Inc.

MonetDB BV

Alon Zakai

enhancements implemented by others

ByteDance, originally Terark

Initial release

2009

2002

2004

2012

2016

Current release

3.10.0, March 2022

4.0

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Mozilla Public License 2.0

Open Source

commercial

restricted open source version available

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

Java

JavaScript

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

SQL-92 is not fully supported

APIs and other access methods

JCache

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JavaScript API

C++ API
Java API

Supported programming languages

Java

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

JavaScript

C++
Java

Server-side scripts

Stored procedures

yes, in SQL, C, R

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

Source-replica replication available in experimental status

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

READ-COMMITTED or SERIALIZED

none

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

except by serializing a db to a file

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

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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