DBMS > FatDB vs. Google Cloud Firestore vs. JSqlDb vs. Spark SQL vs. TimesTen

System Properties Comparison FatDB vs. Google Cloud Firestore vs. JSqlDb vs. Spark SQL vs. TimesTen

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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.

JavaScript Query Language Database, stores JavaScript objects and primitives

Spark SQL is a component on top of 'Spark Core' for structured data processing

In-Memory RDBMS compatible to Oracle

Primary database model

Document store
Key-value store

Document store

Document store
Object oriented DBMS

Relational DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

firebase.google.com/products/firestore

jsqldb.org (offline)

spark.apache.org/sql

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

Technical documentation

firebase.google.com/docs/firestore

spark.apache.org/docs/latest/sql-programming-guide.html

docs.oracle.com/database/timesten-18.1

Developer

FatCloud

Google

Konrad von Backstrom

Apache Software Foundation

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2017

2018

2014

1998

Current release

0.8, December 2018

3.5.0 ( 2.13), September 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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

Scala

Server operating systems

Windows

hosted

Linux
macOS
Windows

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

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

yes

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like DML and DDL statements

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

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

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

JavaScript

Java
Python
R
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

via applications

yes, Firebase Rules & Cloud Functions

functions in JavaScript

PL/SQL

Triggers

yes

via applications

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Can implement custom security layer via applications

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

fine grained access rights according to SQL-standard

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More resources

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