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DBMS > Google Cloud Firestore vs. Hawkular Metrics vs. Microsoft Access vs. Solr

System Properties Comparison Google Cloud Firestore vs. Hawkular Metrics vs. Microsoft Access vs. Solr

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionCloud 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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeTime Series DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitefirebase.google.com/­products/­firestorewww.hawkular.orgwww.microsoft.com/­en-us/­microsoft-365/­accesssolr.apache.org
Technical documentationfirebase.google.com/­docs/­firestorewww.hawkular.org/­hawkular-metrics/­docs/­user-guidedeveloper.microsoft.com/­en-us/­accesssolr.apache.org/­resources.html
DeveloperGoogleCommunity supported by Red HatMicrosoftApache Software Foundation
Initial release2017201419922006
Current release1902 (16.0.11328.20222), March 20199.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infoBundled with Microsoft OfficeOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemshostedLinux
OS X
Windows
Windows infoNot a real database server, but making use of DLLsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes 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.nonoyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnonoyes infobut not compliant to any SQL standardSolr Parallel SQL Interface
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HTTP RESTADO.NET
DAO
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Go
Java
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsnoyes infosince Access 2010 using the ACE-engineJava plugins
Triggersyes, with Cloud Functionsyes infovia Hawkular Alertingyes infosince Access 2010 using the ACE-engineyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandranoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factor infobased on Cassandranoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infobut no files for transaction loggingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.nono infoa simple user-level security was built in till version Access 2003yes

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More resources
Google Cloud FirestoreHawkular MetricsMicrosoft AccessSolr
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