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DBMS > Apache Pinot vs. HugeGraph vs. NSDb vs. Pinecone

System Properties Comparison Apache Pinot vs. HugeGraph vs. NSDb vs. Pinecone

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonHugeGraph  Xexclude from comparisonNSDb  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyA fast-speed and highly-scalable Graph DBMSScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA managed, cloud-native vector database
Primary database modelRelational DBMSGraph DBMSTime Series DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Websitepinot.apache.orggithub.com/­hugegraph
hugegraph.apache.org
nsdb.iowww.pinecone.io
Technical documentationdocs.pinot.apache.orghugegraph.apache.org/­docsnsdb.io/­Architecturedocs.pinecone.io/­docs/­overview
DeveloperApache Software Foundation and contributorsBaiduPinecone Systems, Inc
Initial release2015201820172019
Current release1.0.0, September 20230.9
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava, Scala
Server operating systemsAll OS with a Java JDK11 or higherLinux
macOS
Unix
Linux
macOS
hosted
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringString, Number, Boolean
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 infoalso supports composite index and range indexall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoSQL-like query languageno
APIs and other access methodsJDBCJava API
RESTful HTTP API
TinkerPop Gremlin
gRPC
HTTP REST
WebSocket
RESTful HTTP API
Supported programming languagesGo
Java
Python
Groovy
Java
Python
Java
Scala
Python
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsno
Triggersno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlUsers, roles and permissions

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More resources
Apache PinotHugeGraphNSDbPinecone
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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