DBMS > Google Cloud Firestore vs. MarkLogic vs. Microsoft Azure Data Explorer vs. Oracle vs. Yaacomo

System Properties Comparison Google Cloud Firestore vs. MarkLogic vs. Microsoft Azure Data Explorer vs. Oracle vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Operational and transactional Enterprise NoSQL database

Fully managed big data interactive analytics platform

Widely used RDBMS

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

column oriented

Relational DBMS

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

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

firebase.google.com/products/firestore

www.marklogic.com

azure.microsoft.com/services/data-explorer

www.oracle.com/database

yaacomo.com

Technical documentation

firebase.google.com/docs/firestore

docs.marklogic.com

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

docs.oracle.com/en/database

Developer

Google

MarkLogic Corp.

Microsoft

Oracle

Q2WEB GmbH

Initial release

2017

2001

2019

1980

2009

Current release

11.0, December 2022

cloud service with continuous releases

23c, September 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

restricted free version is available

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

C++

C and C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Android
Linux
Windows

Data scheme

schema-free

Schema can be enforced

Fixed schema with schema-less datatypes (dynamic)

yes

Schemaless in JSON and XML columns

yes

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

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL92

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

yes

APIs and other access methods

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

via XQuery or JavaScript

Yes, possible languages: KQL, Python, R

PL/SQL

also stored procedures in Java possible

Triggers

yes, with Cloud Functions

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

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

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

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

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

can act as a resource manager in an XA/JTA transaction

ACID

isolation level can be parameterized

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, with Range Indexes

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Role-based access control at the document and subdocument levels

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

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