DBMS > Apache Druid vs. Hypertable vs. Microsoft SQL Server vs. Rockset vs. YTsaurus

System Properties Comparison Apache Druid vs. Hypertable vs. Microsoft SQL Server vs. Rockset vs. YTsaurus

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

An open source BigTable implementation based on distributed file systems such as Hadoop

Microsofts flagship relational DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Relational DBMS
Time Series DBMS

Wide column store

Relational DBMS

Document store

Document store
Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.21
Rank	#324	Overall
	#45	Document stores
	#48	Key-value stores

Website

druid.apache.org

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

rockset.com

ytsaurus.tech

Technical documentation

druid.apache.org/docs/latest/design

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

docs.rockset.com

ytsaurus.tech/docs/en

Developer

Apache Software Foundation and contributors

Hypertable Inc.

Microsoft

Rockset

Yandex

Initial release

2012

2009

1989

2019

2023

Current release

29.0.1, April 2024

0.9.8.11, March 2016

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

GNU version 3. Commercial license available

commercial

restricted free version is available

commercial

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

hosted

Ubuntu

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic 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

ingestion from XML files supported

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

all fields are automatically indexed

SQL

Support of SQL

SQL for querying

yes

Read-only SQL queries, including JOINs

YQL, an SQL-based language, is supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

C++ API
Thrift

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

HTTP REST

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C++
Java
Perl
PHP
Python
Ruby

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

Go
Java
JavaScript (Node.js)
Python

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

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

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor on file system level

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

Access Control Lists

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