DBMS > Apache Impala vs. ClickHouse vs. HyperSQL vs. InfluxDB vs. Oracle Coherence

System Properties Comparison Apache Impala vs. ClickHouse vs. HyperSQL vs. InfluxDB vs. Oracle Coherence

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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

DBMS for storing time series, events and metrics

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

Secondary database models

Document store

Time Series DBMS

Spatial DBMS

with GEO package

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

impala.apache.org

clickhouse.com

hsqldb.org

www.influxdata.com/products/influxdb-overview

www.oracle.com/java/coherence

Technical documentation

impala.apache.org/impala-docs.html

clickhouse.com/docs

hsqldb.org/web/hsqlDocsFrame.html

docs.influxdata.com/influxdb

docs.oracle.com/en/middleware/standalone/coherence

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Clickhouse Inc.

Oracle

Initial release

2013

2016

2001

2013

2007

Current release

4.1.0, June 2022

v24.4.1.2088-stable, May 2024

2.7.2, June 2023

2.7.6, April 2024

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

based on BSD license

Open Source

MIT-License; commercial enterprise version available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Java

Server operating systems

Linux

FreeBSD
Linux
macOS

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X

through Homebrew

All OS with a Java VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP API
JSON over UDP

JCache
JPA
RESTful HTTP API

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

All languages supporting JDBC/ODBC
Java

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Java, SQL

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

none

Sharding

in enterprise version only

Sharding

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.

none

selectable replication factor

in enterprise version only

yes, with selectable consistency level

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

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

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

yes

Depending on used storage engine

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

simple rights management via user accounts

authentification to access the cache via certificates or http basic authentication

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