DBMS > KeyDB vs. Microsoft SQL Server vs. Oracle Rdb vs. Sequoiadb vs. Snowflake

System Properties Comparison KeyDB vs. Microsoft SQL Server vs. Oracle Rdb vs. Sequoiadb vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

NewSQL database with distributed OLTP and SQL

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

Primary database model

Key-value store

Relational DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

github.com/Snapchat/KeyDB
keydb.dev

www.microsoft.com/en-us/sql-server

www.oracle.com/database/technologies/related/rdb.html

www.sequoiadb.com

www.snowflake.com

Technical documentation

docs.keydb.dev

learn.microsoft.com/en-US/sql/sql-server

www.oracle.com/database/technologies/related/rdb-doc.html

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.snowflake.net/manuals/index.html

Developer

EQ Alpha Technology Ltd.

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Sequoiadb Ltd.

Snowflake Computing Inc.

Initial release

2019

1989

1984

2013

2014

Current release

SQL Server 2022, November 2022

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

BSD-3

commercial

restricted free version is available

commercial

Open Source

Server: AGPL; Client: Apache V2

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.

Implementation language

C++

Server operating systems

Linux

Linux
Windows

HP Open VMS

Linux

hosted

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

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

Typing

predefined data types such as float or date

partial

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

yes

oid, date, timestamp, binary, regex

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Supported programming languages

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++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C++
Java
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

yes, on a single node

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple password-based access control and ACL

fine grained access rights according to SQL-standard

simple password-based access control

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

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