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DBMS > Databricks vs. Google Cloud Firestore vs. Quasardb vs. Solr

System Properties Comparison Databricks vs. Google Cloud Firestore vs. Quasardb vs. Solr

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonQuasardb  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.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.Distributed, high-performance timeseries databaseA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Relational DBMS
Document storeTime Series DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.databricks.comfirebase.google.com/­products/­firestorequasar.aisolr.apache.org
Technical documentationdocs.databricks.comfirebase.google.com/­docs/­firestoredoc.quasar.ai/­mastersolr.apache.org/­resources.html
DeveloperDatabricksGooglequasardbApache Software Foundation
Initial release2013201720092006
Current release3.14.1, January 20249.6.0, April 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedhostedBSD
Linux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyes 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.yesnonoyes
Secondary indexesyesyesyes infowith tagsyes infoAll search fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query languageSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
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 proceduresuser defined functions and aggregatesyes, Firebase Rules & Cloud FunctionsnoJava plugins
Triggersyes, with Cloud Functionsnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationSource-replica replication with selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflowwith Hadoop integrationspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes
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.Cryptographically strong user authentication and audit trailyes
More information provided by the system vendor
DatabricksGoogle Cloud FirestoreQuasardbSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGoogle Cloud FirestoreQuasardbSolr
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