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DBMS > GeoMesa vs. Spark SQL vs. Speedb vs. Vertica

System Properties Comparison GeoMesa vs. Spark SQL vs. Speedb vs. Vertica

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonSpark SQL  Xexclude from comparisonSpeedb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Spark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for 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 modelSpatial DBMSRelational DBMSKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.21
Rank#315  Overall
#45  Key-value stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.geomesa.orgspark.apache.org/­sqlwww.speedb.iowww.vertica.com
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvertica.com/­documentation
DeveloperCCRi and othersApache Software FoundationSpeedbOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2014201420202005
Current release5.0.0, May 20243.5.0 ( 2.13), September 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0; commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaScalaC++C++
Server operating systemsLinux
OS X
Windows
Linux
Windows
Linux
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 dateyesyesnoyes
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 indexesyesnonoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
Python
R
Scala
C
C++
Go
Java
Perl
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnononoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layeryes, utilizing Spark Corehorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layernoneyesMulti-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 methodsyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACID
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.depending on storage layernoyesno
User concepts infoAccess controlyes infodepending on the DBMS used for storagenonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
GeoMesaSpark SQLSpeedbVertica infoOpenText™ Vertica™
Specific characteristicsSpeedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesSpeedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» more
Fast, 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 modelsOpen source - Speedb OSS is released under an Apache license and can be found on...
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
GeoMesaSpark SQLSpeedbVertica infoOpenText™ Vertica™
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