DBMS > Apache Doris vs. IBM Db2 vs. Microsoft SQL Server vs. Snowflake vs. Sqrrl

System Properties Comparison Apache Doris vs. IBM Db2 vs. Microsoft SQL Server vs. Snowflake vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Common in IBM host environments, 2 different versions for host and Windows/Linux

Microsofts flagship relational DBMS

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS
Spatial DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

www.ibm.com/products/db2

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

www.snowflake.com

sqrrl.com

Technical documentation

github.com/apache/doris/wiki

www.ibm.com/docs/en/db2

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

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation, originally contributed from Baidu

IBM

Microsoft

Snowflake Computing Inc.

Amazon

originally Sqrrl Data, Inc.

Initial release

2017

1983

host version

1989

2014

2012

Current release

1.2.2, February 2023

12.1, October 2016

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free version is available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

C++

Java

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
Windows

hosted

Linux

Data scheme

yes

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

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
MySQL client

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

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

CLI Client
JDBC
ODBC

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

Java

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

JavaScript (Node.js)
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

user defined functions

yes

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

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

only with Windows/Unix/Linux Version

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

yes

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

with separate tools (MQ, InfoSphere)

yes, but depending on the SQL-Server Edition

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

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

fine grained access rights according to SQL-standard

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

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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