DBMS > Firebase Realtime Database vs. GigaSpaces vs. HEAVY.AI vs. RocksDB vs. Snowflake

System Properties Comparison Firebase Realtime Database vs. GigaSpaces vs. HEAVY.AI vs. RocksDB vs. Snowflake

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.

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Spatial DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

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

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.gigaspaces.com

github.com/heavyai/heavydb
www.heavy.ai

rocksdb.org

www.snowflake.com

Technical documentation

firebase.google.com/docs/database

docs.gigaspaces.com/latest/landing.html

docs.heavy.ai

github.com/facebook/rocksdb/wiki

docs.snowflake.net/manuals/index.html

Developer

Google

acquired by Google 2014

Gigaspaces Technologies

HEAVY.AI, Inc.

Facebook, Inc.

Snowflake Computing Inc.

Initial release

2012

2000

2016

2013

2014

Current release

15.5, September 2020

5.10, January 2022

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD

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

Java, C++, .Net

C++ and CUDA

C++

Server operating systems

hosted

Linux
macOS
Solaris
Windows

Linux

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

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

JDBC
ODBC
Thrift
Vega

C++ API
Java API

CLI Client
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

.Net
C++
Java
Python
Scala

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Go
Java
Perl
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

user defined functions

Triggers

Callbacks are triggered when data changes

yes, event driven architecture

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

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

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

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.

yes

User concepts

Access control

yes, based on authentication and database rules

Role-based access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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