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DBMS > Apache Druid vs. Google Cloud Firestore vs. Hazelcast vs. Solr

System Properties Comparison Apache Druid vs. Google Cloud Firestore vs. Hazelcast vs. Solr

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHazelcast  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataCloud 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.A widely adopted in-memory data gridA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMS
Time Series DBMS
Document storeKey-value storeSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitedruid.apache.orgfirebase.google.com/­products/­firestorehazelcast.comsolr.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designfirebase.google.com/­docs/­firestorehazelcast.org/­imdg/­docssolr.apache.org/­resources.html
DeveloperApache Software Foundation and contributorsGoogleHazelcastApache Software Foundation
Initial release2012201720082006
Current release29.0.1, April 20245.3.6, November 20239.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsLinux
OS X
Unix
hostedAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeyes 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 infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL for queryingnoSQL-like query languageSolr Parallel SQL Interface
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes infoEvent Listeners, Executor ServicesJava plugins
Triggersnoyes, with Cloud Functionsyes infoEventsyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replicationyes infoReplicated Mapyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesone or two-phase-commit; repeatable reads; read commitedoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess 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 controlyes

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Apache DruidGoogle Cloud FirestoreHazelcastSolr
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