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DBMS > Heroic vs. Milvus vs. Pinecone vs. SingleStore

System Properties Comparison Heroic vs. Milvus vs. Pinecone vs. SingleStore

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonMilvus  Xexclude from comparisonPinecone  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA DBMS designed for efficient storage of vector data and vector similarity searchesA 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 type
Primary database modelTime Series DBMSVector DBMSVector 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
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score5.60
Rank#62  Overall
#35  Relational DBMS
Websitegithub.com/­spotify/­heroicmilvus.iowww.pinecone.iowww.singlestore.com
Technical documentationspotify.github.io/­heroicmilvus.io/­docs/­overview.mddocs.pinecone.io/­docs/­overviewdocs.singlestore.com
DeveloperSpotifyPinecone Systems, IncSingleStore Inc.
Initial release2014201920192013
Current release2.3.4, January 20248.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0commercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for MilvusSingleStoreDB 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 languageJavaC++, GoC++, Go
Server operating systemsLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
hostedLinux info64 bit version required
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyesVector, Numeric and StringString, Number, Booleanyes
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 indexesyes infovia Elasticsearchnoyes
SQL infoSupport of SQLnononoyes infobut no triggers and foreign keys
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
RESTful HTTP APIRESTful HTTP APICluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesC++
Go
Java
JavaScript (Node.js)
Python
PythonBash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate 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, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlRole based access control and fine grained access rightsFine grained access control via users, groups and roles
More information provided by the system vendor
HeroicMilvusPineconeSingleStore infoformer name was MemSQL
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
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Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
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Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Customers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more
F ree Tier and Enterprise Edition
» more

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More resources
HeroicMilvusPineconeSingleStore infoformer name was MemSQL
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