DBMS > AlaSQL vs. Google Cloud Firestore vs. jBASE vs. Titan vs. VoltDB

System Properties Comparison AlaSQL vs. Google Cloud Firestore vs. jBASE vs. Titan vs. VoltDB

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

JavaScript DBMS library

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

A robust multi-value DBMS comprising development tools and middleware

Titan is a Graph DBMS optimized for distributed clusters.

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Relational 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	7.85
Rank	#51	Overall
	#8	Document stores

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

alasql.org

firebase.google.com/products/firestore

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

github.com/thinkaurelius/titan

www.voltdb.com

Technical documentation

github.com/AlaSQL/alasql

firebase.google.com/docs/firestore

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

github.com/thinkaurelius/titan/wiki

docs.voltdb.com

Developer

Andrey Gershun & Mathias R. Wulff

Google

Rocket Software (formerly Zumasys)

Aurelius, owned by DataStax

VoltDB Inc.

Initial release

2014

2017

1991

2012

2010

Current release

5.7

11.3, April 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache license, version 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

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

hosted

AIX
Linux
Windows

Linux
OS X
Unix
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

Embedded SQL for jBASE in BASIC

yes

only a subset of SQL 99

APIs and other access methods

JavaScript API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

JavaScript

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

.Net
Basic
Jabbascript
Java

Clojure
Java
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Java

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

via pluggable storage backends

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

only for local storage and DOM-storage

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights can be defined down to the item level

User authentification and security via Rexster Graph Server

Users and roles with access to stored procedures

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More resources

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