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DBMS > Amazon DocumentDB vs. Firebase Realtime Database vs. Kdb vs. Microsoft Azure Data Explorer vs. Solr

System Properties Comparison Amazon DocumentDB vs. Firebase Realtime Database vs. Kdb vs. Microsoft Azure Data Explorer vs. Solr

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonKdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.High performance Time Series DBMSFully managed big data interactive analytics platformA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeDocument storeTime Series DBMS
Vector DBMS
Relational DBMS infocolumn orientedSearch engine
Secondary database modelsRelational DBMSDocument store infoIf 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 infothis 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 infosupport 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 infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score13.64
Rank#39  Overall
#6  Document stores
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­documentdbfirebase.google.com/­products/­realtime-databasekx.comazure.microsoft.com/­services/­data-explorersolr.apache.org
Technical documentationaws.amazon.com/­documentdb/­resourcesfirebase.google.com/­docs/­databasecode.kx.comdocs.microsoft.com/­en-us/­azure/­data-explorersolr.apache.org/­resources.html
DeveloperGoogle infoacquired by Google 2014Kx Systems, a division of First Derivatives plcMicrosoftApache Software Foundation
Initial release201920122000 infokdb was released 2000, kdb+ in 200320192006
Current release3.6, May 2018cloud service with continuous releases9.6.0, April 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree 32-bit versioncommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageqJava
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infosupports customizable data types and automatic typing
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesyesyes
Secondary indexesyesyesyes infotable attribute 'grouped'all fields are automatically indexedyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnonoSQL-like query language (q)Kusto Query Language (KQL), SQL subsetSolr Parallel SQL Interface
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Android
iOS
JavaScript API
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Java
JavaScript
Objective-C
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'user defined functionsYes, possible languages: KQL, Python, RJava plugins
TriggersnoCallbacks are triggered when data changesyes infowith viewsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono infosimilar paradigm used for internal processingSpark connector (open source): github.com/­Azure/­azure-kusto-sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyesnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesyes, based on authentication and database rulesrights management via user accountsAzure Active Directory Authenticationyes
More information provided by the system vendor
Amazon DocumentDBFirebase Realtime DatabaseKdbMicrosoft Azure Data ExplorerSolr
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
Amazon DocumentDBFirebase Realtime DatabaseKdbMicrosoft Azure Data ExplorerSolr
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