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DBMS > Apache Druid vs. Microsoft Azure Cosmos DB vs. Postgres-XL vs. Quasardb

System Properties Comparison Apache Druid vs. Microsoft Azure Cosmos DB vs. Postgres-XL vs. Quasardb

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGlobally distributed, horizontally scalable, multi-model database serviceBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresDistributed, high-performance timeseries database
Primary database modelRelational DBMS
Time Series DBMS
Document store
Graph DBMS
Key-value store
Wide column store
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial 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
Score30.39
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score0.56
Rank#253  Overall
#115  Relational DBMS
Score0.19
Rank#330  Overall
#30  Time Series DBMS
Websitedruid.apache.orgazure.microsoft.com/­services/­cosmos-dbwww.postgres-xl.orgquasar.ai
Technical documentationdruid.apache.org/­docs/­latest/­designlearn.microsoft.com/­azure/­cosmos-dbwww.postgres-xl.org/­documentationdoc.quasar.ai/­master
DeveloperApache Software Foundation and contributorsMicrosoftquasardb
Initial release201220142014 infosince 2012, originally named StormDB2009
Current release29.0.0, February 202410 R1, October 20183.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoMozilla public licensecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++
Server operating systemsLinux
OS X
Unix
hostedLinux
macOS
BSD
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes infoJSON typesyesyes infointeger and binary
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.noyes infoXML type, but no XML query functionalityno
Secondary indexesyesyes infoAll properties auto-indexed by defaultyesyes infowith tags
SQL infoSupport of SQLSQL for queryingSQL-like query languageyes infodistributed, parallel query executionSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoJavaScriptuser defined functionsno
TriggersnoJavaScriptyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoImplicit feature of the cloud serviceSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*nowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoMulti-item ACID transactions with snapshot isolation within a partitionACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoTransient mode
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights can be defined down to the item levelfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trail

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More resources
Apache DruidMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBPostgres-XLQuasardb
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