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DBMS > Interbase vs. Microsoft Azure Table Storage vs. Tarantool vs. Valentina Server

System Properties Comparison Interbase vs. Microsoft Azure Table Storage vs. Tarantool vs. Valentina Server

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Editorial information provided by DB-Engines
NameInterbase  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTarantool  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionLight-weight proven RDBMS infooriginally from BorlandA Wide Column Store for rapid development using massive semi-structured datasetsIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsObject-relational database and reports server
Primary database modelRelational DBMSWide column storeDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitewww.embarcadero.com/­products/­interbaseazure.microsoft.com/­en-us/­services/­storage/­tableswww.tarantool.iowww.valentina-db.net
Technical documentationdocs.embarcadero.com/­products/­interbasewww.tarantool.io/­en/­docvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperEmbarcaderoMicrosoftVKParadigma Software
Initial release1984201220081999
Current releaseInterBase 2020, December 20192.10.0, May 20225.7.5
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC and C++
Server operating systemsAndroid
iOS
Linux
OS X
Windows
hostedBSD
Linux
macOS
Linux
OS X
Windows
Data schemeyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesnoFull-featured ANSI SQL supportyes
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIOpen binary protocolODBC
Supported programming languages.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infoInterbase procedure and trigger languagenoLua, C and SQL stored proceduresyes
Triggersyesnoyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
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.Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayes infoMultiversion concurreny controlyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, full featured in-memory storage engine with persistenceyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signaturesAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard

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More resources
InterbaseMicrosoft Azure Table StorageTarantoolValentina Server
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Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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