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DBMS > GeoSpock vs. Google Cloud Datastore vs. Hive vs. Sphinx

System Properties Comparison GeoSpock vs. Google Cloud Datastore vs. Hive vs. Sphinx

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonSphinx  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeRelational DBMSSearch engine
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitegeospock.comcloud.google.com/­datastorehive.apache.orgsphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homesphinxsearch.com/­docs
DeveloperGeoSpockGoogleApache Software Foundation infoinitially developed by FacebookSphinx Technologies Inc.
Initial release200820122001
Current release2.0, September 20193.1.3, April 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
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 languageJava, JavascriptJavaC++
Server operating systemshostedhostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, 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.nono
Secondary indexestemporal, categoricalyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLANSI SQL for query only (using Presto)SQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnousing Google App Engineyes infouser defined functions and integration of map-reduceno
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes infoquery execution via MapReduceno
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.Eventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesno

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More resources
GeoSpockGoogle Cloud DatastoreHiveSphinx
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