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DBMS > OrigoDB vs. Rockset vs. Spark SQL vs. Tarantool

System Properties Comparison OrigoDB vs. Rockset vs. Spark SQL vs. Tarantool

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Editorial information provided by DB-Engines
NameOrigoDB  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionA fully ACID in-memory object graph databaseA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark 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 applications
Primary database modelDocument store
Object oriented DBMS
Document storeRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsRelational DBMS
Search engine
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteorigodb.comrockset.comspark.apache.org/­sqlwww.tarantool.io
Technical documentationorigodb.com/­docsdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tarantool.io/­en/­doc
DeveloperRobert Friberg et alRocksetApache Software FoundationVK
Initial release2009 infounder the name LiveDB201920142008
Current release3.5.0 ( 2.13), September 20232.10.0, May 2022
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C++ScalaC and C++
Server operating systemsLinux
Windows
hostedLinux
OS X
Windows
BSD
Linux
macOS
Data schemeyesschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateUser defined using .NET types and collectionsdynamic typingyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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 infocan be achieved using .NETno infoingestion from XML files supportednono
Secondary indexesyesall fields are automatically indexednoyes
SQL infoSupport of SQLnoRead-only SQL queries, including JOINsSQL-like DML and DDL statementsFull-featured ANSI SQL support
APIs and other access methods.NET Client API
HTTP API
LINQ
HTTP RESTJDBC
ODBC
Open binary protocol
Supported programming languages.NetGo
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyesnonoLua, C and SQL stored procedures
Triggersyes infoDomain Eventsnonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoclient side managed; servers are not synchronizedAutomatic shardingyes, utilizing Spark CoreSharding, 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 nodesSource-replica replicationyesnoneAsynchronous 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 methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 integritydepending on modelnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyes infoWrite ahead logyesyesyes, write ahead logging
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 controlRole based authorizationAccess rights for users and organizations can be defined via Rockset consolenoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
OrigoDBRocksetSpark SQLTarantool
DB-Engines blog posts

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

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