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DBMS > ArcadeDB vs. Databricks vs. Pinecone vs. SpaceTime

System Properties Comparison ArcadeDB vs. Databricks vs. Pinecone vs. SpaceTime

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Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonDatabricks  Xexclude from comparisonPinecone  Xexclude from comparisonSpaceTime  Xexclude from comparison
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenThe 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 managed, cloud-native vector databaseSpaceTime is a spatio-temporal DBMS with a focus on performance.
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document store
Relational DBMS
Vector DBMSSpatial DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Websitearcadedb.comwww.databricks.comwww.pinecone.iowww.mireo.com/­spacetime
Technical documentationdocs.arcadedb.comdocs.databricks.comdocs.pinecone.io/­docs/­overview
DeveloperArcade DataDatabricksPinecone Systems, IncMireo
Initial release2021201320192020
Current releaseSeptember 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsAll OS with a Java VMhostedhostedLinux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesString, 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.noyesnono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like query language, no joinswith Databricks SQLnoA subset of ANSI SQL is implemented
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIRESTful HTTP API
Supported programming languagesJavaPython
R
Scala
PythonC#
C++
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesno
Triggersno
Partitioning methods infoMethods for storing different data on different nodesFixed-grid hypercubes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesReal-time block device replication (DRBD)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes inforelationship in graphsno
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.nonono
User concepts infoAccess controlyes
More information provided by the system vendor
ArcadeDBDatabricksPineconeSpaceTime
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
ArcadeDBDatabricksPineconeSpaceTime
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