DBMS > AlaSQL vs. Couchbase vs. Drizzle vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer

System Properties Comparison AlaSQL vs. Couchbase vs. Drizzle vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Fully managed big data interactive analytics platform

Primary database model

Document store
Relational DBMS

column oriented

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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	16.59
Rank	#36	Overall
	#5	Document stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Website

alasql.org

www.couchbase.com

firebase.google.com/products/realtime-database

azure.microsoft.com/services/data-explorer

Technical documentation

github.com/AlaSQL/alasql

docs.couchbase.com

firebase.google.com/docs/database

docs.microsoft.com/en-us/azure/data-explorer

Developer

Andrey Gershun & Mathias R. Wulff

Couchbase, Inc.

Drizzle project, originally started by Brian Aker

Google

acquired by Google 2014

Microsoft

Initial release

2014

2011

2008

2012

2019

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

7.2.4, September 2012

cloud service with continuous releases

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

GNU GPL

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.

Implementation language

JavaScript

C, C++, Go and Erlang

C++

Server operating systems

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

Linux
OS X
Windows

FreeBSD
Linux
OS X

hosted

Data scheme

schema-free

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-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 fields are automatically indexed

SQL

Support of SQL

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

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

with proprietary extensions

Kusto Query Language (KQL), SQL subset

APIs and other access methods

JavaScript API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JDBC

Android
iOS
JavaScript API
RESTful HTTP API

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

Supported programming languages

JavaScript

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C++
Java
PHP

Java
JavaScript
Objective-C

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

limited functionality with using 'rules'

Yes, possible languages: KQL, Python, R

Triggers

yes

via the TAP protocol

hooks for callbacks inside the server can be used.

Callbacks are triggered when data changes

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

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

yes

Concurrency

Support for concurrent manipulation of data

yes

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

Ephemeral buckets

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes, based on authentication and database rules

Azure Active Directory Authentication

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