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DBMS > Pinecone vs. Quasardb vs. SingleStore vs. Valentina Server

System Properties Comparison Pinecone vs. Quasardb vs. SingleStore vs. Valentina Server

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Editorial information provided by DB-Engines
NamePinecone  Xexclude from comparisonQuasardb  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionA managed, cloud-native vector databaseDistributed, high-performance timeseries databaseMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeObject-relational database and reports server
Primary database modelVector DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score5.60
Rank#62  Overall
#35  Relational DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.pinecone.ioquasar.aiwww.singlestore.comwww.valentina-db.net
Technical documentationdocs.pinecone.io/­docs/­overviewdoc.quasar.ai/­masterdocs.singlestore.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperPinecone Systems, IncquasardbSingleStore Inc.Paradigma Software
Initial release2019200920131999
Current release3.14.1, January 20248.5, January 20245.7.5
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageC++C++, Go
Server operating systemshostedBSD
Linux
OS X
Windows
Linux info64 bit version requiredLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateString, Number, Booleanyes infointeger and binaryyesyes
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.nonono
Secondary indexesyes infowith tagsyesyes
SQL infoSupport of SQLnoSQL-like query languageyes infobut no triggers and foreign keysyes
APIs and other access methodsRESTful HTTP APIHTTP APICluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
ODBC
Supported programming languagesPython.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Bash
C
C#
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnoyesyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoconsistent hashingSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication with selectable replication factorSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationno infocan define user-defined aggregate functions for map-reduce-style calculationsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infoby using LevelDByes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyesyes
User concepts infoAccess controlCryptographically strong user authentication and audit trailFine grained access control via users, groups and rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
PineconeQuasardbSingleStore infoformer name was MemSQLValentina Server
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
PineconeQuasardbSingleStore infoformer name was MemSQLValentina Server
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Recent citations in the news

Pinecone launches serverless edition of its vector database on AWS
22 May 2024, SiliconANGLE News

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

Pinecone Launches Serverless Vector Database for Scalable AI Applications
21 May 2024, Datanami

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21 May 2024, The Wall Street Journal

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6 June 2023, PR Newswire

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SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

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