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DBMS > SiriDB vs. Spark SQL vs. Tarantool vs. TerminusDB

System Properties Comparison SiriDB vs. Spark SQL vs. Tarantool vs. TerminusDB

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Editorial information provided by DB-Engines
NameSiriDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTarantool  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionOpen Source Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processingIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelTime Series DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Graph DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extensionDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.17
Rank#325  Overall
#29  Graph DBMS
Websitesiridb.comspark.apache.org/­sqlwww.tarantool.ioterminusdb.com
Technical documentationdocs.siridb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tarantool.io/­en/­docterminusdb.github.io/­terminusdb/­#
DeveloperCesbitApache Software FoundationVKDataChemist Ltd.
Initial release2017201420082018
Current release3.5.0 ( 2.13), September 20232.10.0, May 202211.0.0, January 2023
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScalaC and C++Prolog, Rust
Server operating systemsLinuxLinux
OS X
Windows
BSD
Linux
macOS
Linux
Data schemeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyes infoNumeric datayesstring, 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.nononono
Secondary indexesyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsFull-featured ANSI SQL supportSQL-like query language (WOQL)
APIs and other access methodsHTTP APIJDBC
ODBC
Open binary protocolOWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
JavaScript
Python
Server-side scripts infoStored proceduresnonoLua, C and SQL stored proceduresyes
Triggersnonoyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Graph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Journaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemCasual 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 integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes infoin-memory journaling
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 persistence
User concepts infoAccess controlsimple rights management via user accountsnoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Role-based access control

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More resources
SiriDBSpark SQLTarantoolTerminusDB infoformer name was DataChemist
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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