DBMS > Apache Drill vs. Microsoft SQL Server vs. Postgres-XL vs. Riak TS

System Properties Comparison Apache Drill vs. Microsoft SQL Server vs. Postgres-XL vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Microsofts flagship relational DBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

drill.apache.org

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

www.postgres-xl.org

Technical documentation

drill.apache.org/docs

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

www.postgres-xl.org/documentation

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation

Microsoft

Open Source, formerly Basho Technologies

Initial release

2012

1989

2014

since 2012, originally named StormDB

2015

Current release

1.20.3, January 2023

SQL Server 2022, November 2022

10 R1, October 2018

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

restricted free version is available

Open Source

Mozilla public license

Open Source

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Erlang

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
macOS

Linux
OS X

Data scheme

schema-free

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

distributed, parallel query execution

yes, limited

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

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

HTTP API
Native Erlang Interface

Supported programming languages

C++

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

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

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

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