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DBMS > Databricks vs. GridGain vs. NSDb vs. TimesTen

System Properties Comparison Databricks vs. GridGain vs. NSDb vs. TimesTen

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonNSDb  Xexclude from comparisonTimesTen  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 IgniteScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelDocument store
Relational DBMS
Columnar
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websitewww.databricks.comwww.gridgain.comnsdb.iowww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmlnsdb.io/­Architecturedocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperDatabricksGridGain Systems, Inc.Oracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2013200720171998
Current releaseGridGain 8.5.1Release 22.1
License infoCommercial or Open Sourcecommercialcommercial, open sourceOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .Net, Python, REST, SQLJava, Scala
Server operating systemshostedLinux
OS X
Solaris
Windows
z/OS
Linux
macOS
IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyes
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.yesyesnono
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
gRPC
HTTP REST
WebSocket
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
Java
Scala
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)noPL/SQL
Triggersyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlRole-based access control
Security Hooks for custom implementations
fine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGridGainNSDbTimesTen
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGridGainNSDbTimesTen
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