DBMS > AlaSQL vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Oracle Berkeley DB vs. Riak TS

System Properties Comparison AlaSQL vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Oracle Berkeley DB vs. Riak TS

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Widely used in-process key-value store

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store
Relational DBMS

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Time Series DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

alasql.org

firebase.google.com/products/realtime-database

cloud.google.com/datastore

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

github.com/AlaSQL/alasql

firebase.google.com/docs/database

cloud.google.com/datastore/docs

docs.oracle.com/cd/E17076_05/html/index.html

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Andrey Gershun & Mathias R. Wulff

Google

acquired by Google 2014

Google

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Open Source, formerly Basho Technologies

Initial release

2014

2012

2008

1994

2015

Current release

18.1.40, May 2020

3.0.0, September 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

commercial license available

Open Source

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

C, Java, C++ (depending on the Berkeley DB edition)

Erlang

Server operating systems

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

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

yes, details here

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

only with the Berkeley DB XML edition

Secondary indexes

yes

restricted

SQL

Support of SQL

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

SQL-like query language (GQL)

yes

SQL interfaced based on SQLite is available

yes, limited

APIs and other access methods

JavaScript API

Android
iOS
JavaScript API
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

Supported programming languages

JavaScript

Java
JavaScript
Objective-C

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

limited functionality with using 'rules'

using Google App Engine

Erlang

Triggers

yes

Callbacks are triggered when data changes

Callbacks using the Google Apps Engine

yes

only for the SQL API

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using Paxos

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

links between datasets can be stored

Transaction concepts

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

yes

only for local storage and DOM-storage

yes

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

yes, based on authentication and database rules

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

More information provided by the system vendor

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