DBMS > Apache Cassandra vs. FoundationDB vs. TimescaleDB

System Properties Comparison Apache Cassandra vs. FoundationDB vs. TimescaleDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Ordered key-value store. Core features are complimented by layers.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Wide column store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Time Series DBMS

Secondary database models

Vector DBMS

starting with release V5

Relational DBMS

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

Score	97.94
Rank	#11	Overall
	#1	Wide column stores

Score	0.92
Rank	#196	Overall
	#33	Document stores
	#29	Key-value stores
	#91	Relational DBMS

Score	3.74
Rank	#74	Overall
	#5	Time Series DBMS

Website

cassandra.apache.org

github.com/apple/foundationdb

www.timescale.com

Technical documentation

cassandra.apache.org/doc/latest

apple.github.io/foundationdb

docs.timescale.com

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

FoundationDB

Timescale

Initial release

2008

2013

2017

Current release

5.0-rc1, July 2024

6.2.28, November 2020

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Apache 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

C++

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

some layers support typing

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

yes

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

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

supported in specific SQL layer only

yes

full PostgreSQL SQL syntax

APIs and other access methods

Proprietary protocol

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

in SQL-layer only

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes

Source-replica replication with hot standby and reads on replicas

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

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

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.

User concepts

Access control

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

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

Market metrics

Apache 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...
» more

News

Instantly Chat with Your PDFs Using Langflow
12 December 2024

Shaping the Wild in Las Vegas: An AWS re:Invent Recap
11 December 2024

Announcing 12 Days of Codemas: The DataStax Holiday Giveaway!
9 December 2024

Build Equitable and Validated Generative AI with Wikidata and DataStax Leveraging NVIDIA Technologies
3 December 2024

Securely Connecting to Astra DB with AWS
2 December 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.