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DBMS > Graph Engine vs. Pinecone vs. Spark SQL vs. YDB

System Properties Comparison Graph Engine vs. Pinecone vs. Spark SQL vs. YDB

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonPinecone  Xexclude from comparisonSpark SQL  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA managed, cloud-native vector databaseSpark SQL is a component on top of 'Spark Core' for structured data processingA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelGraph DBMS
Key-value store
Vector DBMSRelational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitewww.graphengine.iowww.pinecone.iospark.apache.org/­sqlgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationwww.graphengine.io/­docs/­manualdocs.pinecone.io/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperMicrosoftPinecone Systems, IncApache Software FoundationYandex
Initial release2010201920142019
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoApache 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CScala
Server operating systems.NEThostedLinux
OS X
Windows
Linux
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesString, Number, Booleanyesyes
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 indexesnoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (YQL)
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIJDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC#
C++
F#
Visual Basic
PythonJava
Python
R
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyesnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlnoAccess rights defined for Yandex Cloud users

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More resources
Graph Engine infoformer name: TrinityPineconeSpark SQLYDB
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