DBMS > AlaSQL vs. Ehcache vs. HEAVY.AI vs. RocksDB

System Properties Comparison AlaSQL vs. Ehcache vs. HEAVY.AI vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A widely adopted Java cache with tiered storage options

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

alasql.org

www.ehcache.org

github.com/heavyai/heavydb
www.heavy.ai

rocksdb.org

Technical documentation

github.com/AlaSQL/alasql

www.ehcache.org/documentation

docs.heavy.ai

github.com/facebook/rocksdb/wiki

Developer

Andrey Gershun & Mathias R. Wulff

Terracotta Inc, owned by Software AG

HEAVY.AI, Inc.

Facebook, Inc.

Initial release

2014

2009

2016

2013

Current release

3.10.0, March 2022

5.10, January 2022

8.11.4, April 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD

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

JavaScript

Java

C++ and CUDA

C++

Server operating systems

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

All OS with a Java VM

Linux

Data scheme

schema-free

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

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

APIs and other access methods

JavaScript API

JCache

JDBC
ODBC
Thrift
Vega

C++ API
Java API

Supported programming languages

JavaScript

Java

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

Sharding

Round robin

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

yes

supports JTA and can work as an XA resource

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

using a tiered cache-storage approach

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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