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DBMS > Pinecone vs. SingleStore vs. Vitess

System Properties Comparison Pinecone vs. SingleStore vs. Vitess

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Editorial information provided by DB-Engines
NamePinecone  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionA managed, cloud-native vector 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 typeScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelVector DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score5.60
Rank#62  Overall
#35  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.pinecone.iowww.singlestore.comvitess.io
Technical documentationdocs.pinecone.io/­docs/­overviewdocs.singlestore.comvitess.io/­docs
DeveloperPinecone Systems, IncSingleStore Inc.The Linux Foundation, PlanetScale
Initial release201920132013
Current release8.5, January 202415.0.2, December 2022
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnono
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++, GoGo
Server operating systemshostedLinux info64 bit version requiredDocker
Linux
macOS
Data schemeyesyes
Typing infopredefined data types such as float or dateString, 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.nono
Secondary indexesyesyes
SQL infoSupport of SQLnoyes infobut no triggers and foreign keysyes infowith proprietary extensions
APIs and other access methodsRESTful HTTP APICluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesPythonBash
C
C#
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesyes infoproprietary syntax
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infohash partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infostores two copies of each physical data partition on two separate nodesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infocan define user-defined aggregate functions for map-reduce-style calculationsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyes 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.noyesyes
User concepts infoAccess controlFine grained access control via users, groups and rolesUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
PineconeSingleStore infoformer name was MemSQLVitess
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
PineconeSingleStore infoformer name was MemSQLVitess
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022,  Akmal Chaudhri, SingleStore (sponsor) 

Cloud-Based Analytics With SingleStoreDB
9 June 2022,  Akmal Chaudhri, SingleStore (sponsor) 

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022,  Akmal Chaudhri, SingleStore (sponsor) 

show all

Recent citations in the news

Pinecone’s new serverless database may see few takers, analysts say
17 January 2024, InfoWorld

Pinecone Brings Serverless To Vector Databases
16 January 2024, Forbes

Pinecone Unveils Serverless Vector Database for Enhanced AI Applications
16 January 2024, Datanami

Pinecone: New vector database architecture a 'breakthrough' to curb AI hallucinations
16 January 2024, VentureBeat

Reimagining Vector Databases for the Generative AI Era with Pinecone Serverless on AWS | Amazon Web Services
21 March 2024, AWS Blog

provided by Google News

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

SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development
24 January 2024, Business Wire

SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files
29 January 2024, Blocks & Files

Leveraging SingleStoreDB Cloud Private Connectivity Using AWS PrivateLink | Amazon Web Services
6 December 2023, AWS Blog

Announcing watsonx.ai and SingleStore for generative AI applications
15 November 2023, IBM

provided by Google News

Vitess, the database clustering system powering YouTube, graduates CNCF incubation
5 November 2019, SiliconANGLE News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

The ultimate MySQL database platform — PlanetScale
20 June 2018, planetscale.com

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube — now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

provided by Google News



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