DBMS > EXASOL vs. FoundationDB vs. RocksDB vs. Snowflake

System Properties Comparison EXASOL vs. FoundationDB vs. RocksDB vs. Snowflake

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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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Key-value store

Relational DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.exasol.com

github.com/apple/foundationdb

rocksdb.org

www.snowflake.com

Technical documentation

www.exasol.com/resources

apple.github.io/foundationdb

github.com/facebook/rocksdb/wiki

docs.snowflake.net/manuals/index.html

Developer

Exasol

FoundationDB

Facebook, Inc.

Snowflake Computing Inc.

Initial release

2000

2013

2014

Current release

6.2.28, November 2020

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

Data scheme

yes

schema-free

some layers support schemas

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

some layers support typing

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

supported in specific SQL layer only

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

C++ API
Java API

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
C++
Go
Java
Perl
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in SQL-layer only

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

in SQL-layer only

yes

Transaction concepts

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

ACID

yes

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, groups and roles according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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