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DBMS > Databricks vs. Google Cloud Datastore vs. GridGain vs. Sphinx vs. SWC-DB

System Properties Comparison Databricks vs. Google Cloud Datastore vs. GridGain vs. Sphinx vs. SWC-DB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonSphinx  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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 PlatformGridGain is an in-memory computing platform, built on Apache IgniteOpen source search engine for searching in data from different sources, e.g. relational databasesA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Relational DBMS
Document storeKey-value store
Relational DBMS
Search engineWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.08
Rank#364  Overall
#13  Wide column stores
Websitewww.databricks.comcloud.google.com/­datastorewww.gridgain.comsphinxsearch.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.databricks.comcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmlsphinxsearch.com/­docs
DeveloperDatabricksGoogleGridGain Systems, Inc.Sphinx Technologies Inc.Alex Kashirin
Initial release20132008200720012020
Current releaseGridGain 8.5.13.5.1, February 20230.5, April 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC++C++
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesno
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.yesnoyesno
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)SQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocolProprietary protocol
Thrift
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App Engineyes (compute grid and cache interceptors can be used instead)nono
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)nono
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 TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsno
More information provided by the system vendor
DatabricksGoogle Cloud DatastoreGridGainSphinxSWC-DB infoSuper Wide Column Database
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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