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DBMS > Databricks vs. GridGain vs. Sadas Engine vs. Teradata Aster vs. TinkerGraph

System Properties Comparison Databricks vs. GridGain vs. Sadas Engine vs. Teradata Aster vs. TinkerGraph

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonSadas Engine  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTinkerGraph  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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 IgniteSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsPlatform for big data analytics on multistructured data sources and typesA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Relational DBMSRelational DBMSGraph 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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitewww.databricks.comwww.gridgain.comwww.sadasengine.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperDatabricksGridGain Systems, Inc.SADAS s.r.l.Teradata
Initial release20132007200620052009
Current releaseGridGain 8.5.18.0
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree trial version availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC++Java
Server operating systemshostedLinux
OS X
Solaris
Windows
AIX
Linux
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesyesnoyes infoin Aster File Storeno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLyesyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
ODBC
OLE DB
TinkerPop 3
Supported programming languagesPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C#
C++
Java
Python
R
Groovy
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)noR packagesno
Triggersyes (cache interceptors and events)nonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)noneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)noyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationnone
Foreign keys infoReferential integritynoyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infomanaged by 'Learn by Usage'noyes
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardno
More information provided by the system vendor
DatabricksGridGainSadas EngineTeradata AsterTinkerGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGridGainSadas EngineTeradata AsterTinkerGraph
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