DBMS > Apache Cassandra vs. Dgraph vs. Riak KV vs. Tigris

System Properties Comparison Apache Cassandra vs. Dgraph vs. Riak KV vs. Tigris

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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

Distributed and scalable native Graph DBMS

Distributed, fault tolerant key-value store

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Wide column store

Graph DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	0.05
Rank	#359	Overall
	#50	Document stores
	#52	Key-value stores
	#23	Search engines
	#37	Time Series DBMS

Website

cassandra.apache.org

dgraph.io

www.tigrisdata.com

Technical documentation

cassandra.apache.org/doc/latest

dgraph.io/docs

www.tiot.jp/riak-docs/riak/kv/latest

www.tigrisdata.com/docs

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Dgraph Labs, Inc.

OpenSource, formerly Basho Technologies

Tigris Data, Inc.

Initial release

2008

2016

2009

2022

Current release

5.0-rc1, July 2024

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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

Erlang

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Linux
OS X

Linux
macOS
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

restricted

yes

SQL

Support of SQL

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

APIs and other access methods

Proprietary protocol

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

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

HTTP API
Native Erlang Interface

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

yes

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Synchronous replication via Raft

selectable replication factor

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

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

yes, using FoundationDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users can be defined per object

Planned for future releases

yes, using Riak Security

Access rights for users and roles

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

Apache 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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