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DBMS > Databricks vs. Google Cloud Datastore vs. RethinkDB vs. SwayDB

System Properties Comparison Databricks vs. Google Cloud Datastore vs. RethinkDB vs. SwayDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRethinkDB  Xexclude from comparisonSwayDB  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for the Web with a mechanism to push updated query results to applications in realtime.An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelDocument store
Relational DBMS
Document storeDocument storeKey-value store
Secondary database modelsSpatial 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
Score4.47
Rank#76  Overall
#12  Document stores
Score2.74
Rank#105  Overall
#19  Document stores
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitewww.databricks.comcloud.google.com/­datastorerethinkdb.comswaydb.simer.au
Technical documentationdocs.databricks.comcloud.google.com/­datastore/­docsrethinkdb.com/­docs
DeveloperDatabricksGoogleThe Linux Foundation infosince July 2017Simer Plaha
Initial release2013200820092018
Current release2.4.1, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Scala
Server operating systemshostedhostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyes infostring, binary, float, bool, date, geometryno
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.yesnonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (GQL)nono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Java
Kotlin
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App Engineno
TriggersCallbacks using the Google Apps EngineClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding inforange basednone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic single-document operationsAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC basedyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousers and table-level permissionsno
More information provided by the system vendor
DatabricksGoogle Cloud DatastoreRethinkDBSwayDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGoogle Cloud DatastoreRethinkDBSwayDB
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