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DBMS > Pinecone vs. Spark SQL vs. TDSQL for MySQL vs. TerarkDB

System Properties Comparison Pinecone vs. Spark SQL vs. TDSQL for MySQL vs. TerarkDB

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Editorial information provided by DB-Engines
NamePinecone  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionA managed, cloud-native vector databaseSpark SQL is a component on top of 'Spark Core' for structured data processingA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelVector DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.pinecone.iospark.apache.org/­sqlwww.tencentcloud.com/­products/­dcdbgithub.com/­bytedance/­terarkdb
Technical documentationdocs.pinecone.io/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042bytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperPinecone Systems, IncApache Software FoundationTencentByteDance, originally Terark
Initial release2019201420132016
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++
Server operating systemshostedLinux
OS X
Windows
hosted
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateString, Number, Booleanyesyesno
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 indexesnoyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBC
ODBC
C++ API
Java API
Supported programming languagesPythonJava
Python
R
Scala
C
C#
C++
Java
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresnoyesno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreAutomatic shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
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 datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlnoUsers with fine-grained authorization conceptno

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More resources
PineconeSpark SQLTDSQL for MySQLTerarkDB
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