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DBMS > Druid vs. RocksDB vs. Vertica

System Properties Comparison Druid vs. RocksDB vs. Vertica

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Editorial information provided by DB-Engines
NameDruid  Xexclude from comparisonRocksDB  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionOpen-source analytics data store designed for OLAP queries on timeseries dataEmbeddable persistent key-value store optimized for fast storage (flash and RAM)Columnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.79
Rank#117  Overall
#58  Relational DBMS
#7  Time Series DBMS
Score2.52
Rank#103  Overall
#19  Key-value stores
Score22.55
Rank#29  Overall
#17  Relational DBMS
Websitedruid.apache.orgrocksdb.orgwww.vertica.com
Technical documentationdruid.apache.org/­docs/­latest/­designgithub.com/­facebook/­rocksdb/­wikiwww.vertica.com/­documentation/­vertica
DeveloperMetamarkets Group and contributorsFacebook, Inc.Vertica / Micro Focus infoprior to that Hewlett Packard
Initial release201220132005
Current release6.3.6, October 2019Vertica Analytics Platform 9.2.x, March 2019
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoBSDcommercial 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 languageJavaC++
Server operating systemsLinux
OS X
Unix
Linux
Data schemeyes infoschema-less columns are supportedschema-freeyes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesnoyes
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.nonoyes
Secondary indexesyesnono infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLSQL support via Apache Calcite adapternoyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsJSON over HTTPC++ API
Java API
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnonoyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneMaster-master 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 integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID
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 extensionsnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DruidRocksDBVertica 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
DruidRocksDBVertica infoVertica Analytics Platform
Recent citations in the news

What's Behind Lyft's Choices in Big Data Tech
10 May 2019, Datanami

Imply launches with $2M to commercialize the Druid open-source data store
19 October 2015, VentureBeat

Hadoop Creator Yahoo Finds It's Not Enough, Turns to Druid
30 July 2015, ADT Magazine

Yahoo Casts Real-Time OLAP Queries with Druid
4 August 2015, Datanami

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23 September 2019, Business Wire

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17 September 2019, Yahoo Finance

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