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DBMS > Apache Druid vs. Interbase vs. Microsoft Azure Table Storage vs. Prometheus vs. Splice Machine

System Properties Comparison Apache Druid vs. Interbase vs. Microsoft Azure Table Storage vs. Prometheus vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonInterbase  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonPrometheus  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataLight-weight proven RDBMS infooriginally from BorlandA Wide Column Store for rapid development using massive semi-structured datasetsOpen-source Time Series DBMS and monitoring systemOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSWide column storeTime Series DBMSRelational DBMS
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
Score4.61
Rank#72  Overall
#39  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitedruid.apache.orgwww.embarcadero.com/­products/­interbaseazure.microsoft.com/­en-us/­services/­storage/­tablesprometheus.iosplicemachine.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.embarcadero.com/­products/­interbaseprometheus.io/­docssplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsEmbarcaderoMicrosoftSplice Machine
Initial release20121984201220152014
Current release29.0.1, April 2024InterBase 2020, December 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCGoJava
Server operating systemsLinux
OS X
Unix
Android
iOS
Linux
OS X
Windows
hostedLinux
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesNumeric data onlyyes
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.nono infoexport as XML data possiblenono infoImport of XML data possible
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLSQL for queryingyesnonoyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
RESTful HTTP APIRESTful HTTP/JSON APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoInterbase procedure and trigger languagenonoyes infoJava
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneSharding infoImplicit feature of the cloud serviceShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesInterbase Change Viewsyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoby FederationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signaturesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache DruidInterbaseMicrosoft Azure Table StoragePrometheusSplice Machine
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