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DBMS > Amazon Redshift vs. Databricks vs. DataFS vs. Graph Engine vs. Hypertable

System Properties Comparison Amazon Redshift vs. Databricks vs. DataFS vs. Graph Engine vs. Hypertable

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonDatabricks  Xexclude from comparisonDataFS  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHypertable  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionLarge scale data warehouse service for use with business intelligence toolsThe 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.All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineAn open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelRelational DBMSDocument store
Relational DBMS
Object oriented DBMSGraph DBMS
Key-value store
Wide column store
Secondary database modelsGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Websiteaws.amazon.com/­redshiftwww.databricks.comnewdatabase.comwww.graphengine.io
Technical documentationdocs.aws.amazon.com/­redshiftdocs.databricks.comdev.mobiland.com/­Overview.xspwww.graphengine.io/­docs/­manual
DeveloperAmazon (based on PostgreSQL)DatabricksMobiland AGMicrosoftHypertable Inc.
Initial release20122013201820102009
Current release1.1.263, October 20220.9.8.11, March 2016
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoMIT LicenseOpen Source infoGNU version 3. Commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC.NET and CC++
Server operating systemshostedhostedWindows.NETLinux
OS X
Windows infoan inofficial Windows port is available
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.noyesnono
Secondary indexesrestrictedyesnorestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardwith Databricks SQLnonono
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
.NET Client API
Proprietary client DLL
WinRT client
RESTful HTTP APIC++ API
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C
C#
C++
VB.Net
C#
C++
F#
Visual Basic
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin Pythonuser defined functions and aggregatesyesno
Triggersnono, except callback-events from server when changes happenednono
Partitioning methods infoMethods for storing different data on different nodesShardingProprietary Sharding systemhorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardWindows-Profileno
More information provided by the system vendor
Amazon RedshiftDatabricksDataFSGraph Engine infoformer name: TrinityHypertable
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon RedshiftDatabricksDataFSGraph Engine infoformer name: TrinityHypertable
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