DBMS > AlaSQL vs. Amazon SimpleDB vs. ClickHouse vs. ITTIA

System Properties Comparison AlaSQL vs. Amazon SimpleDB vs. ClickHouse vs. ITTIA

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

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.

Edge Time Series DBMS with Real-Time Stream Processing

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Website

alasql.org

aws.amazon.com/simpledb

clickhouse.com

www.ittia.com

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/simpledb

clickhouse.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Amazon

Clickhouse Inc.

ITTIA L.L.C.

Initial release

2014

2007

2016

2007

Current release

v24.4.2.141-stable, June 2024

8.7

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache 2.0

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
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.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

JavaScript

C++

C and C++

Server operating systems

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

hosted

FreeBSD
Linux
macOS

Linux
Windows

Data scheme

schema-free

yes

Fixed schema

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

All columns are indexed automatically

yes

SQL

Support of SQL

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

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

JavaScript API

RESTful HTTP API

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

JDBC
ODBC
RESTful HTTP API
WebSocket

Supported programming languages

JavaScript

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

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++
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

key based and custom

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

Concurrent data updates can be detected by the application

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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 and roles can be defined via the AWS Identity and Access Management (IAM)

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.

Database file passwords

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