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DBMS > Bangdb vs. Microsoft Azure AI Search vs. Pinecone vs. Spark SQL

System Properties Comparison Bangdb vs. Microsoft Azure AI Search vs. Pinecone vs. Spark SQL

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPinecone  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphSearch-as-a-service for web and mobile app developmentA managed, cloud-native vector databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Search engineVector DBMSRelational DBMS
Secondary database modelsSpatial DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebangdb.comazure.microsoft.com/­en-us/­services/­searchwww.pinecone.iospark.apache.org/­sql
Technical documentationdocs.bangdb.comlearn.microsoft.com/­en-us/­azure/­searchdocs.pinecone.io/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBMicrosoftPinecone Systems, IncApache Software Foundation
Initial release2012201520192014
Current releaseBangDB 2.0, October 2021V13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++Scala
Server operating systemsLinuxhostedhostedLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesString, 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 infosecondary, composite, nested, reverse, geospatialyesno
SQL infoSupport of SQLSQL like support with command line toolnonoSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol
RESTful HTTP API
RESTful HTTP APIRESTful HTTP APIJDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
C#
Java
JavaScript
Python
PythonJava
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersyes, Notifications (with Streaming only)nono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modenonono
User concepts infoAccess controlyes (enterprise version only)yes infousing Azure authenticationno

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More resources
BangdbMicrosoft Azure AI SearchPineconeSpark SQL
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