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DBMS > Databricks vs. EJDB vs. Tigris

System Properties Comparison Databricks vs. EJDB vs. Tigris

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEJDB  Xexclude from comparisonTigris  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.Embeddable document-store database library with JSON representation of queries (in MongoDB style)A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelDocument store
Relational DBMS
Document storeDocument store
Key-value store
Search engine
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score99.29
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score0.11
Rank#339  Overall
#47  Document stores
Score0.06
Rank#352  Overall
#50  Document stores
#53  Key-value stores
#23  Search engines
#35  Time Series DBMS
Websitewww.databricks.comgithub.com/­Softmotions/­ejdbwww.tigrisdata.com
Technical documentationdocs.databricks.comgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdwww.tigrisdata.com/­docs
DeveloperDatabricksSoftmotionsTigris Data, Inc.
Initial release201320122022
License infoCommercial or Open SourcecommercialOpen Source infoGPLv2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC
Server operating systemshostedserver-lessLinux
macOS
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes
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.yesno
Secondary indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
in-process shared libraryCLI Client
gRPC
RESTful HTTP API
Supported programming languagesPython
R
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyes
Durability infoSupport for making data persistentyesyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlnoAccess rights for users and roles

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DatabricksEJDBTigris
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