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DBMS > Databricks vs. GridGain vs. Hive vs. InfinityDB vs. TinkerGraph

System Properties Comparison Databricks vs. GridGain vs. Hive vs. InfinityDB vs. TinkerGraph

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonHive  Xexclude from comparisonInfinityDB  Xexclude from comparisonTinkerGraph  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 Ignitedata warehouse software for querying and managing large distributed datasets, built on HadoopA Java embedded Key-Value Store which extends the Java Map interfaceA 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 DBMSKey-value storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.34
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score1.59
Rank#158  Overall
#26  Key-value stores
#73  Relational DBMS
Score64.82
Rank#18  Overall
#12  Relational DBMS
Score0.09
Rank#357  Overall
#53  Key-value stores
Score0.13
Rank#347  Overall
#33  Graph DBMS
Websitewww.databricks.comwww.gridgain.comhive.apache.orgboilerbay.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homeboilerbay.com/­infinitydb/­manual
DeveloperDatabricksGridGain Systems, Inc.Apache Software Foundation infoinitially developed by FacebookBoiler Bay Inc.
Initial release20132007201220022009
Current releaseGridGain 8.5.13.1.3, April 20224.0
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2commercialOpen 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++, .NetJavaJavaJava
Server operating systemshostedLinux
OS X
Solaris
Windows
All OS with a Java VMAll OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-free
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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 indexesyesyesyesno infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
TinkerPop 3
Supported programming languagesPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
PHP
Python
JavaGroovy
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)yes infouser defined functions and integration of map-reducenono
Triggersyes (cache interceptors and events)nonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)selectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDnone
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilityyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infoOptimistic locking for transactions; no isolation for bulk loadsno
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.noyesnoyes
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights for users, groups and rolesnono
More information provided by the system vendor
DatabricksGridGainHiveInfinityDBTinkerGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGridGainHiveInfinityDBTinkerGraph
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