DBMS > Apache Druid vs. Apache Impala vs. Heroic vs. Microsoft SQL Server vs. TempoIQ

System Properties Comparison Apache Druid vs. Apache Impala vs. Heroic vs. Microsoft SQL Server vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be 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

Analytic DBMS for Hadoop

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Microsofts flagship relational DBMS

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Document store

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	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

druid.apache.org

impala.apache.org

github.com/spotify/heroic

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

tempoiq.com (offline)

Technical documentation

druid.apache.org/docs/latest/design

impala.apache.org/impala-docs.html

spotify.github.io/heroic

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

Developer

Apache Software Foundation and contributors

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Spotify

Microsoft

TempoIQ

Initial release

2012

2013

2014

1989

2012

Current release

29.0.1, April 2024

4.1.0, June 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2

Open Source

Apache 2.0

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++

Java

C++

Server operating systems

Linux
OS X
Unix

Linux

Linux
Windows

Data scheme

yes

schema-less columns are supported

yes

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

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL for querying

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

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

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages supporting JDBC/ODBC

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

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

Triggers

yes

Realtime Alerts

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

yes

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

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

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

simple authentication-based access control

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