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DBMS > Databricks vs. EDB Postgres vs. Pinecone

System Properties Comparison Databricks vs. EDB Postgres vs. Pinecone

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEDB Postgres  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.The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.A managed, cloud-native vector database
Primary database modelDocument store
Relational DBMS
Relational DBMSVector DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Websitewww.databricks.comwww.enterprisedb.comwww.pinecone.io
Technical documentationdocs.databricks.comwww.enterprisedb.com/­docsdocs.pinecone.io/­docs/­overview
DeveloperDatabricksEnterpriseDBPinecone Systems, Inc
Initial release201320052019
Current release14, December 2021
License infoCommercial or Open Sourcecommercialcommercial infoBSD for PostgreSQL-componentscommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC
Server operating systemshostedLinux
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesString, 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.yesyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infostandard with numerous extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoby hash, list or range
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksEDB PostgresPinecone
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEDB PostgresPinecone
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