DBMS > Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. OpenSearch vs. Oracle Berkeley DB

System Properties Comparison Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. OpenSearch vs. Oracle Berkeley DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Widely used in-process key-value store

Primary database model

column oriented

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

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

Vector DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

firebase.google.com/products/realtime-database

azure.microsoft.com/services/data-explorer

github.com/opensearch-project
opensearch.org

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

firebase.google.com/docs/database

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

opensearch.org/docs/latest

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Google

acquired by Google 2014

Microsoft

Amazon Web Services

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2012

2019

2021

1994

Current release

cloud service with continuous releases

2.5.0, January 2023

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

commercial license available

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.

Aiven for OpenSearch: Fully managed open source search and analytics suite. Out-of-the-box integrations get you up and running in a couple of clicks.

Implementation language

Java

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

All OS with a Java VM

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

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

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

all fields are automatically indexed

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

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

Java API
RESTful HTTP/JSON API

Supported programming languages

Java
JavaScript
Objective-C

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Yes, possible languages: KQL, Python, R

yes

Triggers

Callbacks are triggered when data changes

yes

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

yes

by using the 'percolation' feature

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency
Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

Transaction concepts

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

yes

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

yes, based on authentication and database rules

Azure Active Directory Authentication

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.