DBMS > AlaSQL vs. Datomic vs. Ehcache vs. Google BigQuery vs. RethinkDB

System Properties Comparison AlaSQL vs. Datomic vs. Ehcache vs. Google BigQuery vs. RethinkDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A widely adopted Java cache with tiered storage options

Large scale data warehouse service with append-only tables

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Document store
Relational DBMS

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

alasql.org

www.datomic.com

www.ehcache.org

cloud.google.com/bigquery

rethinkdb.com

Technical documentation

github.com/AlaSQL/alasql

docs.datomic.com

www.ehcache.org/documentation

cloud.google.com/bigquery/docs

rethinkdb.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Cognitect

Terracotta Inc, owned by Software AG

Google

The Linux Foundation

since July 2017

Initial release

2014

2012

2009

2010

2009

Current release

1.0.6735, June 2023

3.10.0, March 2022

2.4.1, August 2020

License

Commercial or Open Source

Open Source

MIT-License

commercial

limited edition free

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java, Clojure

Java

C++

Server operating systems

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

All OS with a Java VM

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

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

yes

APIs and other access methods

JavaScript API

RESTful HTTP API

JCache

RESTful HTTP/JSON API

Supported programming languages

JavaScript

Clojure
Java

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

in JavaScript

Triggers

yes

By using transaction functions

yes

Cache Event Listeners

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

by using Terracotta Server

none

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

by using Terracotta Server

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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

ACID

yes

supports JTA and can work as an XA resource

Since BigQuery is designed for querying data

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

users and table-level permissions

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