DBMS > Firebase Realtime Database vs. Hazelcast vs. Linter vs. OmniSci

System Properties Comparison Firebase Realtime Database vs. Hazelcast vs. Linter vs. OmniSci

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Editorial information provided by DB-Engines

Name

Description

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

A widely adopted in-memory data grid

RDBMS for high security requirements

A high performance, in-memory, column-oriented RDBMS, designed to run on GPUs

Primary database model

Document store

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

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

Score	16.92
Rank	#38	Overall
	#5	Document stores

Score	9.27
Rank	#46	Overall
	#5	Key-value stores

Score	0.08
Rank	#312	Overall
	#137	Relational DBMS

Score	1.24
Rank	#153	Overall
	#75	Relational DBMS

Website

firebase.google.com/products/realtime-database

hazelcast.com

linter.ru/en

www.omnisci.com

Technical documentation

firebase.google.com/docs/database

hazelcast.org/imdg/docs

docs.omnisci.com

Developer

Google

acquired by Google 2014

Hazelcast

relex.ru/en

MapD Technologies, Inc.

Initial release

2012

2008

1990

2016

Current release

4.2, March 2021

5.5, January 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache Version 2; enterprise edition 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 and C++

C++ and CUDA

Server operating systems

hosted

All OS with a Java VM

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
ODBC
Thrift

Supported programming languages

Java
JavaScript
Objective-C

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Event Listeners, Executor Services

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

Callbacks are triggered when data changes

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

one or two-phase-commit; repeatable reads; read commited

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.

yes

User concepts

Access control

yes, based on authentication and database rules

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Hazelcast is an in-memory computing platform that runs applications with extremely...
» more

Competitive advantages

Hazelcast has an optimized, multi-threaded architecture that enables the highest...
» more

Typical application scenarios

Hazelcast powers many types of large-scale, data processing applications. A sample...
» more

Key customers

Hazelcast customers include 50 of the world’s largest financial services companies,...
» more

Licensing and pricing models

Hazelcast provides both open source and commercial software. The open source offering...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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13 April 2021, SoccerNurds

GPU Database Market Recent Trends and Developments By 2028: Kinetica, OmniSci, SQream, Neo4j, NVIDIA, Brytlyt, Blazegraph, BlazingDB, etc. – SoccerNurds
10 April 2021, SoccerNurds

GPU Database Market Analysis, Geographical Segmentation, Drivers, Challenges, Trends and Forecast| Kinetica, OmniSci, SQream, Neo4j, NVIDIA, Brytlyt, Blazegraph, BlazingDB, Zilliz, and Jedox. Moreover, the other prospective players in the GPU database market are HeteroDB, H2O.ai, FASTDATA.io, Fuzzy Logix, and Anaconda.
7 April 2021, SoccerNurds

provided by Google News

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