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DBMS > Databricks vs. GridGain vs. STSdb

System Properties Comparison Databricks vs. GridGain vs. STSdb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonSTSdb  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.GridGain is an in-memory computing platform, built on Apache IgniteKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.33
Rank#19  Overall
#3  Document stores
#13  Relational DBMS
Score2.41
Rank#129  Overall
#26  Key-value stores
#63  Relational DBMS
Score0.33
Rank#317  Overall
#46  Key-value stores
Websitedatabricks.comwww.gridgain.comgithub.com/­STSSoft/­STSdb4
Technical documentationdatabricks.com/­documentationwww.gridgain.com/­docs/­latest
DeveloperDatabricksGridGain Systems, Inc.STS Soft SC
Initial release201320072011
Current releaseGridGain 8.5.14.0.8, September 2015
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC#
Server operating systemshostedLinux
OS X
Solaris
Windows
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes infoprimitive types and user defined types (classes)
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
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
.NET Client API
Supported programming languagesPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)no
Triggersyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyes
User concepts infoAccess controlSecurity Hooks for custom implementationsno

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More resources
DatabricksGridGainSTSdb
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