DBMS > Cassandra vs. Firebird vs. GridDB vs. Rockset

System Properties Comparison Cassandra vs. Firebird vs. GridDB vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Firebird is an open source RDBMS forked from Borland's InterBase

Scalable in-memory time series database optimized for IoT and Big Data

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Key-value store
Relational DBMS

Relational DBMS
Search engine

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

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

Technical documentation

cassandra.apache.org/doc/latest

www.firebirdsql.org/en/reference-manuals

docs.griddb.net

docs.rockset.com

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Firebird Foundation

Toshiba Corporation

Rockset

Initial release

2008

2000

As fork of Borland's InterBase

2013

2019

Current release

4.1.3, July 2023

5.0.0, January 2024

5.1, August 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Initial Developer's Public License

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C and C++

C++

Server operating systems

BSD
Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

yes

SQL92, SQL-like TQL (Toshiba Query Language)

Read-only SQL queries, including JOINs

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP REST

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

PSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

ACID at container level

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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

Access rights for users can be defined per object

Users with fine-grained authorization concept

Access rights for users can be defined per database

Access rights for users and organizations can be defined via Rockset console

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
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GitHub trending repository
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Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
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