DBMS > AnzoGraph DB vs. Cassandra vs. Firebird vs. Rockset

System Properties Comparison AnzoGraph DB vs. Cassandra vs. Firebird vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

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

Relational DBMS
Search engine

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

cambridgesemantics.com/anzograph

cassandra.apache.org

www.firebirdsql.org

rockset.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

cassandra.apache.org/doc/latest

www.firebirdsql.org/en/reference-manuals

docs.rockset.com

Developer

Cambridge Semantics

Apache Software Foundation

Apache top level project, originally developped by Facebook

Firebird Foundation

Rockset

Initial release

2018

2008

2000

As fork of Borland's InterBase

2019

Current release

2.3, January 2021

4.1.3, July 2023

5.0.0, January 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache version 2

Open Source

Initial Developer's Public License

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

Linux

BSD
Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

SPARQL and SPARQL* as primary query language. Cypher preview.

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

yes

Read-only SQL queries, including JOINs

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

Proprietary protocol

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

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

HTTP REST

Supported programming languages

C++
Java
Python

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

PSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

no "single point of failure"

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

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

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

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 and roles

Access rights for users can be defined per object

Users with fine-grained authorization concept

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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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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News

An Introduction to David Jones-Gilardi, Developer Relations
11 June 2024

Introducing Tejas Kumar, Developer Relations Engineer
7 June 2024

Indexing All of Wikipedia on a Laptop
5 June 2024

An Introduction to Phil Nash, Developer Relations
3 June 2024

Focus on Creativity, Not Clusters: DataStax Mission Control in Action!
30 May 2024

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