DBMS > Cassandra vs. HEAVY.AI vs. Rockset vs. SiriDB vs. TigerGraph

System Properties Comparison Cassandra vs. HEAVY.AI vs. Rockset vs. SiriDB vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

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

Open Source Time Series DBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Spatial 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	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

cassandra.apache.org

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

rockset.com

siridb.com

www.tigergraph.com

Technical documentation

cassandra.apache.org/doc/latest

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

HEAVY.AI, Inc.

Rockset

Cesbit

Initial release

2008

2016

2019

2017

Current release

4.1.3, July 2023

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

MIT 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 CUDA

C++

Server operating systems

BSD
Linux
OS X
Windows

Linux

hosted

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

dynamic typing

yes

Numeric data

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.

ingestion from XML files supported

Secondary indexes

restricted

only equality queries, not always the best performing solution

all fields are automatically indexed

yes

SQL

Support of SQL

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

yes

Read-only SQL queries, including JOINs

SQL-like query language (GSQL)

APIs and other access methods

Proprietary protocol

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

JDBC
ODBC
Thrift
Vega

HTTP REST

HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/Thrift
Python

Go
Java
JavaScript (Node.js)
Python

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

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Round robin

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Atomicity and isolation are supported for single operations

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

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

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

simple rights management via user accounts

Role-based access control

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.
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Licensing and pricing models

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