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

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

Editorial information provided by DB-Engines
NameInterbase  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonPrometheus  Xexclude from comparisonRavenDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionLight-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 Operational and Transactional Enterprise NoSQL Document DatabaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSWide column storeTime Series DBMSDocument storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score2.92
Rank#101  Overall
#18  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.embarcadero.com/­products/­interbaseazure.microsoft.com/­en-us/­services/­storage/­tablesprometheus.ioravendb.netsplicemachine.com
Technical documentationdocs.embarcadero.com/­products/­interbaseprometheus.io/­docsravendb.net/­docssplicemachine.com/­how-it-works
DeveloperEmbarcaderoMicrosoftHibernating RhinosSplice Machine
Initial release19842012201520102014
Current releaseInterBase 2020, December 20195.4, July 20223.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoAGPL version 3, commercial license availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCGoC#Java
Server operating systemsAndroid
iOS
Linux
OS X
Windows
hostedLinux
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlynoyes
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.no infoexport as XML data possiblenono infoImport of XML data possible
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLyesnonoSQL-like query language (RQL)yes
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIRESTful HTTP/JSON API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languages.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
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoInterbase procedure and trigger languagenonoyesyes infoJava
Triggersyesnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInterbase Change Viewsyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoby FederationMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencynoneDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingnoACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of datayes infoMultiversion concurreny controlyesyesyesyes, 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.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signaturesnoAuthorization levels configured per client per databaseAccess rights for users, groups and roles according to SQL-standard

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More resources
InterbaseMicrosoft Azure Table StoragePrometheusRavenDBSplice Machine
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