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DBMS > Databricks vs. GigaSpaces vs. Google Cloud Spanner vs. Hive

System Properties Comparison Databricks vs. GigaSpaces vs. Google Cloud Spanner vs. Hive

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHive  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.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelDocument store
Relational DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Websitewww.databricks.comwww.gigaspaces.comcloud.google.com/­spannerhive.apache.org
Technical documentationdocs.databricks.comdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­spanner/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperDatabricksGigaspaces TechnologiesGoogleApache Software Foundation infoinitially developed by Facebook
Initial release2013200020172012
Current release15.5, September 20203.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJava
Server operating systemshostedLinux
macOS
Solaris
Windows
hostedAll OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-99 for query and DML statementsyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
Thrift
Supported programming languagesPython
R
Scala
.Net
C++
Java
Python
Scala
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnoyes infouser defined functions and integration of map-reduce
Triggersyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication with 3 replicas for regional instances.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsyes infousing Google Cloud Dataflowyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoStrict serializable isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesno
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles
More information provided by the system vendor
DatabricksGigaSpacesGoogle Cloud SpannerHive
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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