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DBMS > Apache Druid vs. Google Cloud Datastore vs. RocksDB vs. Solr

System Properties Comparison Apache Druid vs. Google Cloud Datastore vs. RocksDB vs. Solr

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRocksDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEmbeddable persistent key-value store optimized for fast storage (flash and RAM)A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMS
Time Series DBMS
Document storeKey-value storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.33
Rank#99  Overall
#51  Relational DBMS
#7  Time Series DBMS
Score4.87
Rank#78  Overall
#12  Document stores
Score4.52
Rank#80  Overall
#10  Key-value stores
Score43.91
Rank#24  Overall
#3  Search engines
Websitedruid.apache.orgcloud.google.com/­datastorerocksdb.orgsolr.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docsgithub.com/­facebook/­rocksdb/­wikisolr.apache.org/­resources.html
DeveloperApache Software Foundation and contributorsGoogleFacebook, Inc.Apache Software Foundation
Initial release2012200820132006
Current release29.0.0, February 20248.10.0, December 20239.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoBSDOpen 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 languageJavaC++Java
Server operating systemsLinux
OS X
Unix
hostedLinuxAll 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 dateyesyes, details herenoyes 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.nononoyes
Secondary indexesyesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL for queryingSQL-like query language (GQL)noSolr Parallel SQL Interface
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Java API
Java API
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
Perl
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnousing Google App EnginenoJava plugins
TriggersnoCallbacks using the Google Apps Engineyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using Paxosyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyesoptimistic 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.nonoyesyes
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 (IAM)noyes

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More resources
Apache DruidGoogle Cloud DatastoreRocksDBSolr
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