DBMS > Apache Doris vs. Firebase Realtime Database vs. GigaSpaces vs. Hypertable vs. RocksDB

System Properties Comparison Apache Doris vs. Firebase Realtime Database vs. GigaSpaces vs. Hypertable vs. RocksDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Primary database model

Relational DBMS

Document store

Document store
Object oriented DBMS

Values are user defined objects

Wide column store

Key-value store

Secondary database models

Graph DBMS
Search engine

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

doris.apache.org
github.com/apache/doris

firebase.google.com/products/realtime-database

www.gigaspaces.com

rocksdb.org

Technical documentation

github.com/apache/doris/wiki

firebase.google.com/docs/database

docs.gigaspaces.com/latest/landing.html

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation, originally contributed from Baidu

Google

acquired by Google 2014

Gigaspaces Technologies

Hypertable Inc.

Facebook, Inc.

Initial release

2017

2012

2000

2009

2013

Current release

1.2.2, February 2023

15.5, September 2020

0.9.8.11, March 2016

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

GNU version 3. Commercial license available

Open Source

BSD

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

Java, C++, .Net

C++

Server operating systems

Linux

hosted

Linux
macOS
Solaris
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

yes

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

SQL-99 for query and DML statements

APIs and other access methods

JDBC
MySQL client

Android
iOS
JavaScript API
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

C++ API
Thrift

C++ API
Java API

Supported programming languages

Java

Java
JavaScript
Objective-C

.Net
C++
Java
Python
Scala

C++
Java
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor on file system level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

yes

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

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Role-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.