DBMS > ClickHouse vs. Kinetica vs. LeanXcale vs. RavenDB vs. SAP HANA

System Properties Comparison ClickHouse vs. Kinetica vs. LeanXcale vs. RavenDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

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.

Fully vectorized database across both GPUs and CPUs

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Open Source Operational and Transactional Enterprise NoSQL Document Database

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store

Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS
Time Series DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	16.20
Rank	#37	Overall
	#23	Relational DBMS

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	0.35
Rank	#283	Overall
	#41	Key-value stores
	#128	Relational DBMS

Score	3.01
Rank	#101	Overall
	#17	Document stores

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Website

www.sap.com/products/hana.html

Technical documentation

Developer

Clickhouse Inc.

Kinetica

LeanXcale

Hibernating Rhinos

SAP

Initial release

2016

2012

2015

2010

Current release

v24.3.2.23-lts, April 2024

7.1, August 2021

5.4, July 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

AGPL version 3, commercial license available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based 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++

C, C++

Server operating systems

FreeBSD
Linux
macOS

Linux

Linux
macOS
Raspberry Pi
Windows

Appliance or cloud-service

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like DML and DDL statements

yes

through Apache Derby

SQL-like query language (RQL)

yes

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
ODBC

Supported programming languages

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++
Java
JavaScript (Node.js)
Python

C
Java
Scala

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes

SQLScript, R

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

GPU vRAM or System RAM

yes

User concepts

Access control

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.

Access rights for users and roles on table level

Authorization levels configured per client per database

yes

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