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DBMS > GeoSpock vs. HBase vs. Vertica vs. Yaacomo

System Properties Comparison GeoSpock vs. HBase vs. Vertica vs. Yaacomo

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHBase  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionSpatial and temporal data processing engine for extreme data scaleWide-column store based on Apache Hadoop and on concepts of BigTableCloud 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.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSWide column storeRelational DBMS infoColumn orientedRelational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score27.97
Rank#26  Overall
#2  Wide column stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegeospock.comhbase.apache.orgwww.vertica.comyaacomo.com
Technical documentationhbase.apache.org/­book.htmlvertica.com/­documentation
DeveloperGeoSpockApache Software Foundation infoApache top-level project, originally developed by PowersetOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release200820052009
Current release2.0, September 20192.3.4, January 202112.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud serviceyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptJavaC++
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
LinuxAndroid
Linux
Windows
Data schemeyesschema-free, schema definition possibleYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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.nononono
Secondary indexestemporal, categoricalnoNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLANSI SQL for query only (using Presto)noFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsJDBCJava API
RESTful HTTP API
Thrift
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardinghorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)ACIDACID
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.noyesnoyes
User concepts infoAccess controlAccess rights for users can be defined per tableAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
GeoSpockHBaseVertica infoOpenText™ Vertica™Yaacomo
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...
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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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More resources
GeoSpockHBaseVertica infoOpenText™ Vertica™Yaacomo
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