DBMS > Apache Druid vs. Elasticsearch vs. Hypertable vs. Microsoft SQL Server vs. Quasardb

System Properties Comparison Apache Druid vs. Elasticsearch vs. Hypertable vs. Microsoft SQL Server vs. Quasardb

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

Microsofts flagship relational DBMS

Distributed, high-performance timeseries database

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

druid.apache.org

www.elastic.co/elasticsearch

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

quasar.ai

Technical documentation

druid.apache.org/docs/latest/design

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

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

doc.quasar.ai/master

Developer

Apache Software Foundation and contributors

Elastic

Hypertable Inc.

Microsoft

quasardb

Initial release

2012

2010

2009

1989

2009

Current release

29.0.1, April 2024

8.6, January 2023

0.9.8.11, March 2016

SQL Server 2022, November 2022

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Elastic License

Open Source

GNU version 3. Commercial license available

commercial

restricted free version is available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

All search fields are automatically indexed

restricted

only exact value or prefix value scans

yes

with tags

SQL

Support of SQL

SQL for querying

SQL-like query language

yes

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java API
RESTful HTTP/JSON API

C++ API
Thrift

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

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

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

Triggers

yes

by using the 'percolation' feature

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

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

selectable replication factor on file system level

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate 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

by using LevelDB

In-memory capabilities

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

Memcached and Redis integration

yes

Transient mode

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

Cryptographically strong user authentication and audit trail

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