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DBMS > Apache Druid vs. Geode vs. Microsoft Azure Table Storage vs. Prometheus

System Properties Comparison Apache Druid vs. Geode vs. Microsoft Azure Table Storage vs. Prometheus

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGeode  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA Wide Column Store for rapid development using massive semi-structured datasetsOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeWide column storeTime Series 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
Score1.86
Rank#134  Overall
#24  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websitedruid.apache.orggeode.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tablesprometheus.io
Technical documentationdruid.apache.org/­docs/­latest/­designgeode.apache.org/­docsprometheus.io/­docs
DeveloperApache Software Foundation and contributorsOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Microsoft
Initial release2012200220122015
Current release29.0.1, April 20241.1, February 2017
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGo
Server operating systemsLinux
OS X
Unix
All OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesNumeric data only
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.nononono infoImport of XML data possible
Secondary indexesyesnonono
SQL infoSupport of SQLSQL for queryingSQL-like query language (OQL)nono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java Client API
Memcached protocol
RESTful HTTP API
RESTful HTTP APIRESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersnoyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistencynone
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes, on a single nodeoptimistic lockingno
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.noyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights per client and object definableAccess rights based on private key authentication or shared access signaturesno

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More resources
Apache DruidGeodeMicrosoft Azure Table StoragePrometheus
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