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DBMS > GeoSpock vs. Hive vs. Rockset vs. Vertica

System Properties Comparison GeoSpock vs. Hive vs. Rockset vs. Vertica

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHive  Xexclude from comparisonRockset  Xexclude from comparisonVertica infoOpenText™ Vertica™  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 scaledata warehouse software for querying and managing large distributed datasets, built on HadoopA scalable, reliable search and analytics service in the cloud, built on RocksDBCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS infoColumn oriented
Secondary database modelsTime Series DBMSRelational DBMS
Search engine
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegeospock.comhive.apache.orgrockset.comwww.vertica.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.rockset.comvertica.com/­documentation
DeveloperGeoSpockApache Software Foundation infoinitially developed by FacebookRocksetOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201220192005
Current release2.0, September 20193.1.3, April 202212.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnoyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptJavaC++C++
Server operating systemshostedAll OS with a Java VMhostedLinux
Data schemeyesyesschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesdynamic typingyes
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 infoingestion from XML files supportedno
Secondary indexestemporal, categoricalyesall fields are automatically indexedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLANSI SQL for query only (using Presto)SQL-like DML and DDL statementsRead-only SQL queries, including JOINsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBCJDBC
ODBC
Thrift
HTTP RESTADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC++
Java
PHP
Python
Go
Java
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingAutomatic shardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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.nono
User concepts infoAccess controlAccess rights for users can be defined per tableAccess rights for users, groups and rolesAccess rights for users and organizations can be defined via Rockset consolefine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
GeoSpockHiveRocksetVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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GeoSpockHiveRocksetVertica infoOpenText™ Vertica™
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