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DBMS > Databricks vs. Drizzle vs. Microsoft Azure Table Storage

System Properties Comparison Databricks vs. Drizzle vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded 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.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument store
Relational DBMS
Relational DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitewww.databricks.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.databricks.com
DeveloperDatabricksDrizzle project, originally started by Brian AkerMicrosoft
Initial release201320082012
Current release7.2.4, September 2012
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedFreeBSD
Linux
OS X
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes
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.yesno
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCRESTful HTTP API
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersno infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic locking
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.nono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights based on private key authentication or shared access signatures
More information provided by the system vendor
DatabricksDrizzleMicrosoft Azure Table Storage
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDrizzleMicrosoft Azure Table Storage
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