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DBMS > Apache Druid vs. Valentina Server vs. Vertica

System Properties Comparison Apache Druid vs. Valentina Server vs. Vertica

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonValentina Server  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataObject-relational database and reports serverColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.69
Rank#103  Overall
#51  Relational DBMS
#7  Time Series DBMS
Score0.22
Rank#277  Overall
#130  Relational DBMS
Score20.95
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgwww.valentina-db.netwww.vertica.com
Technical documentationdruid.apache.org/­docs/­latest/­designvalentina-db.com/­docs/­dokuwiki/­v5/­doku.phpwww.vertica.com/­docs/­10.0.x/­HTML/­Content/­Home.htm
DeveloperApache Software Foundation and contributorsParadigma SoftwareVertica / Micro Focus infoprior to that Hewlett Packard
Initial release201219992005
Current release0.20.1, January 20215.7.5Vertica 10.0 Software, May 2020
Vertica for SQL on Hadoop 10.0 Software, May 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoAvailable on all major clouds - Amazon AWS, Microsoft Azure and Google Cloud Platform
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesyes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyesyes
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.noyes
Secondary indexesyesyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLSQL for queryingyesyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ODBCADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnoyesyes
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache DruidValentina ServerVertica infoVertica Analytics Platform
Specific characteristicsColumnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesPerformance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» 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 available
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache DruidValentina ServerVertica infoVertica Analytics Platform
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Job opportunities

Sales Development Representative
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