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DBMS > Apache Druid vs. Google Cloud Spanner vs. Microsoft Azure Table Storage vs. searchxml

System Properties Comparison Apache Druid vs. Google Cloud Spanner vs. Microsoft Azure Table Storage vs. searchxml

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonsearchxml  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A Wide Column Store for rapid development using massive semi-structured datasetsDBMS for structured and unstructured content wrapped with an application server
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSWide column storeNative XML DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.00
Rank#383  Overall
#7  Native XML DBMS
#25  Search engines
Websitedruid.apache.orgcloud.google.com/­spannerazure.microsoft.com/­en-us/­services/­storage/­tableswww.searchxml.net/­category/­products
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­spanner/­docswww.searchxml.net/­support/­handouts
DeveloperApache Software Foundation and contributorsGoogleMicrosoftinformationpartners gmbh
Initial release2012201720122015
Current release29.0.1, April 20241.0
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinux
OS X
Unix
hostedhostedWindows
Data schemeyes infoschema-less columns are supportedyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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
SQL infoSupport of SQLSQL for queryingyes infoQuery statements complying to ANSI 2011nono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
RESTful HTTP APIRESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresnononoyes infoon the application server
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication with 3 replicas for regional instances.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infosychronisation to multiple collections
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationoptimistic lockingmultiple readers, single writer
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.nononono
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)Access rights based on private key authentication or shared access signaturesDomain, group and role-based access control at the document level and for application services

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More resources
Apache DruidGoogle Cloud SpannerMicrosoft Azure Table Storagesearchxml
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