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DBMS > Druid vs. GridGain vs. Vertica

System Properties Comparison Druid vs. GridGain vs. Vertica

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Editorial information provided by DB-Engines
NameDruid  Xexclude from comparisonGridGain  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionOpen-source analytics data store designed for OLAP queries on timeseries dataGridGain is an in-memory computing platform, built on Apache IgniteColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.83
Rank#115  Overall
#57  Relational DBMS
#7  Time Series DBMS
Score1.60
Rank#124  Overall
#22  Key-value stores
#61  Relational DBMS
Score22.17
Rank#30  Overall
#18  Relational DBMS
Websitedruid.apache.orgwww.gridgain.comwww.vertica.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.gridgain.com/­docs/­latestwww.vertica.com/­documentation/­vertica
DeveloperMetamarkets Group and contributorsGridGain Systems, Inc.Vertica / Micro Focus infoprior to that Hewlett Packard
Initial release201220072005
Current releaseGridGain 8.5.1Vertica Analytics Platform 9.2.x, March 2019
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoavailable on Amazon AWS and Microsoft Azure
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .Net
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
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.noyesyes
Secondary indexesyesyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLSQL support via Apache Calcite adapterANSI-99 for query and DML statements, subset of DDLyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsJSON over HTTPHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)yes
Triggersnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes (replicated cache)Master-master replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)yes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 controlno infoavailable via extensionsSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DruidGridGainVertica 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
DruidGridGainVertica infoVertica Analytics Platform
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