DBMS > Amazon Redshift vs. FoundationDB vs. KeyDB vs. Splice Machine vs. Tigris

System Properties Comparison Amazon Redshift vs. FoundationDB vs. KeyDB vs. Splice Machine vs. Tigris

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

Large scale data warehouse service for use with business intelligence tools

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

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

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Key-value store

Relational DBMS

Document store
Key-value store
Search engine
Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.06
Rank	#185	Overall
	#31	Document stores
	#28	Key-value stores
	#85	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

aws.amazon.com/redshift

github.com/apple/foundationdb

github.com/Snapchat/KeyDB
keydb.dev

splicemachine.com

www.tigrisdata.com

Technical documentation

docs.aws.amazon.com/redshift

apple.github.io/foundationdb

docs.keydb.dev

splicemachine.com/how-it-works

www.tigrisdata.com/docs

Developer

Amazon (based on PostgreSQL)

FoundationDB

EQ Alpha Technology Ltd.

Splice Machine

Tigris Data, Inc.

Initial release

2012

2013

2019

2014

2022

Current release

6.2.28, November 2020

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD-3

Open Source

AGPL 3.0, commercial license available

Open Source

Apache Version 2.0

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.

Implementation language

C++

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

some layers support schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

some layers support typing

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

supported in specific SQL layer only

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
Native Spark Datasource
ODBC

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

user defined functions

in Python

in SQL-layer only

Lua

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

in SQL-layer only

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

yes, using FoundationDB

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control and ACL

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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