DBMS > AlaSQL vs. Apache Drill vs. Apache Impala vs. ClickHouse vs. Drizzle

System Properties Comparison AlaSQL vs. Apache Drill vs. Apache Impala vs. ClickHouse vs. Drizzle

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

JavaScript DBMS library

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Primary database model

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store

Time Series DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

drill.apache.org/docs

impala.apache.org/impala-docs.html

clickhouse.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Clickhouse Inc.

Drizzle project, originally started by Brian Aker

Initial release

2014

2012

2013

2016

2008

Current release

1.20.3, January 2023

4.1.0, June 2022

v24.4.1.2088-stable, May 2024

7.2.4, September 2012

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

GNU GPL

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

Linux

FreeBSD
Linux
macOS

FreeBSD
Linux
OS X

Data scheme

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 SQL99, but no user access control, stored procedures and host language bindings.

SQL SELECT statement is SQL:2003 compliant

SQL-like DML and DDL statements

Close to ANSI SQL (SQL/JSON + extensions)

yes

with proprietary extensions

APIs and other access methods

JavaScript API

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

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

JDBC

Supported programming languages

JavaScript

C++

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++
Java
PHP

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

key based and custom

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

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

Multi-source replication
Source-replica replication

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

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

Depending on the underlying data source

yes

In-memory capabilities

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

yes

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

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.

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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