DBMS > Apache Impala vs. ClickHouse vs. SAP IQ vs. SiteWhere vs. Snowflake

System Properties Comparison Apache Impala vs. ClickHouse vs. SAP IQ vs. SiteWhere vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Columnar RDBMS optimized for Big Data analytics

M2M integration platform for persisting/querying time series data

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

Primary database model

Relational DBMS

column-oriented

Time Series DBMS

Relational DBMS

Secondary database models

Document store

Time Series DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

impala.apache.org

clickhouse.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

github.com/sitewhere/sitewhere

www.snowflake.com

Technical documentation

impala.apache.org/impala-docs.html

clickhouse.com/docs

help.sap.com/docs/SAP_IQ

sitewhere1.sitewhere.io/index.html

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Clickhouse Inc.

SAP, formerly Sybase

SiteWhere

Snowflake Computing Inc.

Initial release

2013

2016

1994

2010

2014

Current release

4.1.0, June 2022

v24.4.1.2088-stable, May 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C++

Java

Server operating systems

Linux

FreeBSD
Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

hosted

Data scheme

yes

predefined scheme

yes

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

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

SQL-like DML and DDL statements

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

JDBC
ODBC

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

ADO.NET
JDBC
ODBC
RESTful HTTP API

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

based on HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

SAP/Sybase Replication Server

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual 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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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

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