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DBMS > Cachelot.io vs. Databricks vs. STSdb vs. Vertica

System Properties Comparison Cachelot.io vs. Databricks vs. STSdb vs. Vertica

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Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonDatabricks  Xexclude from comparisonSTSdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionIn-memory caching systemThe 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.Key-Value Store with special method for indexing infooptimized for high performance using a special indexing methodCloud 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 modelKey-value storeDocument store
Relational DBMS
Key-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
Score0.00
Rank#383  Overall
#60  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitecachelot.iowww.databricks.comgithub.com/­STSSoft/­STSdb4www.vertica.com
Technical documentationdocs.databricks.comvertica.com/­documentation
DeveloperDatabricksSTS Soft SCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201320112005
Current release4.0.8, September 201512.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicensecommercialOpen Source infoGPLv2, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono 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 languageC++C#C++
Server operating systemsFreeBSD
Linux
OS X
hostedWindowsLinux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesYes, 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 datenoyes infoprimitive types and user defined types (classes)yes
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.noyesno
Secondary indexesnoyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnowith Databricks SQLnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsMemcached protocolJDBC
ODBC
RESTful HTTP API
.NET Client APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
Python
R
Scala
C#
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnoneMulti-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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentnoyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Cachelot.ioDatabricksSTSdbVertica infoOpenText™ Vertica™
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Cachelot.ioDatabricksSTSdbVertica infoOpenText™ Vertica™
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