DBMS > Altibase vs. ClickHouse vs. Snowflake vs. Solr vs. SQream DB

System Properties Comparison Altibase vs. ClickHouse vs. Snowflake vs. Solr vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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.

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

A widely used distributed, scalable search engine based on Apache Lucene

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

clickhouse.com/docs

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

docs.sqream.com

Developer

Altibase

Clickhouse Inc.

Snowflake Computing Inc.

Apache Software Foundation

SQream Technologies

Initial release

1999

2016

2014

2006

2017

Current release

v7.3, 2023, August 2023

v24.4.1.2088-stable, May 2024

9.6.0, April 2024

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2

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.

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

C++, CUDA, Haskell, Java, Scala

Server operating systems

AIX
HP-UX
Linux

FreeBSD
Linux
macOS

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

yes

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

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

yes, ANSI Standard SQL Types

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

SQL

Support of SQL

ANSI SQL-92

Close to ANSI SQL (SQL/JSON + extensions)

yes

Solr Parallel SQL Interface

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

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

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

.Net
JDBC
ODBC

Supported programming languages

C
C++
Java

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

JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

user defined functions

Java plugins

user defined functions in Python

Triggers

yes

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

yes

Sharding

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

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

optimistic locking

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

fine grained access rights according to SQL-standard

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.

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

yes

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