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DBMS > Databricks vs. HugeGraph vs. Microsoft Azure AI Search vs. Pinecone

System Properties Comparison Databricks vs. HugeGraph vs. Microsoft Azure AI Search vs. Pinecone

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentA managed, cloud-native vector database
Primary database modelDocument store
Relational DBMS
Graph DBMSSearch engineVector DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score3.23
Rank#92  Overall
#3  Vector DBMS
Websitewww.databricks.comgithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchwww.pinecone.io
Technical documentationdocs.databricks.comhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchdocs.pinecone.io/­docs/­overview
DeveloperDatabricksBaiduMicrosoftPinecone Systems, Inc
Initial release2013201820152019
Current release0.9V1
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedLinux
macOS
Unix
hostedhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesString, 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.yesnonono
Secondary indexesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLwith Databricks SQLnonono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIRESTful HTTP API
Supported programming languagesPython
R
Scala
Groovy
Java
Python
C#
Java
JavaScript
Python
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesasynchronous Gremlin script jobsno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlUsers, roles and permissionsyes infousing Azure authentication
More information provided by the system vendor
DatabricksHugeGraphMicrosoft Azure AI SearchPinecone
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHugeGraphMicrosoft Azure AI SearchPinecone
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