DBMS > Elasticsearch vs. FatDB vs. Firebase Realtime Database vs. RocksDB vs. TypeDB

System Properties Comparison Elasticsearch vs. FatDB vs. Firebase Realtime Database vs. RocksDB vs. TypeDB

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.

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

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

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

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Search engine

Document store
Key-value store

Document store

Key-value store

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

www.elastic.co/elasticsearch

firebase.google.com/products/realtime-database

rocksdb.org

typedb.com

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

firebase.google.com/docs/database

github.com/facebook/rocksdb/wiki

typedb.com/docs

Developer

Elastic

FatCloud

Google

acquired by Google 2014

Facebook, Inc.

Vaticle

Initial release

2010

2012

2013

2016

Current release

8.6, January 2023

9.2.1, May 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

BSD

Open Source

GPL Version 3, commercial licenses available

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

Java

C++

Java

Server operating systems

All OS with a Java VM

Windows

hosted

Linux

Linux
OS X
Windows

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

Via inetgration in SQL Server

APIs and other access methods

Java API
RESTful HTTP/JSON API

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

Android
iOS
JavaScript API
RESTful HTTP API

C++ API
Java API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

C
C++
Go
Java
Perl
Python
Ruby

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

via applications

limited functionality with using 'rules'

Triggers

yes

by using the 'percolation' feature

yes

via applications

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

substituted by the relationship feature

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

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

Can implement custom security layer via applications

yes, based on authentication and database rules

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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