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DBMS > Apache Druid vs. Hive vs. TimescaleDB vs. UniData,UniVerse vs. Vertica

System Properties Comparison Apache Druid vs. Hive vs. TimescaleDB vs. UniData,UniVerse vs. Vertica

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHive  Xexclude from comparisonTimescaleDB  Xexclude from comparisonUniData,UniVerse  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality datadata warehouse software for querying and managing large distributed datasets, built on HadoopA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLMultiValue database and application server with SQL mapping layer and meta database capabilitiesCloud 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 modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSMultivalue DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score2.85
Rank#98  Overall
#1  Multivalue DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitedruid.apache.orghive.apache.orgwww.timescale.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidatawww.vertica.com
Technical documentationdruid.apache.org/­docs/­latest/­designcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.timescale.comdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidatavertica.com/­documentation
DeveloperApache Software Foundation and contributorsApache Software Foundation infoinitially developed by FacebookTimescaleRocket SoftwareOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122012201719852005
Current release29.0.1, April 20243.1.3, April 20222.15.0, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open Source infoApache 2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono 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 languageJavaJavaCCC++
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux
OS X
Windows
AIX
HP-UX
Linux
Solaris
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesyesschema-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 dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesoptionalyes
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 indexesyesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
.Net
Basic infoU2 Basic
C
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyesyes infoU2 Basicyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingyes, across time and space (hash partitioning) attributesnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorSource-replica replication with hot standby and reads on replicas infoSource-replica replicationMulti-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 methodsnoyes infoquery execution via MapReducenonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID infoconfigurableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and rolesfine grained access rights according to SQL-standardAccess rights according to SQL-standard and operating system basedfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache DruidHiveTimescaleDBUniData,UniVerseVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-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...
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More resources
Apache DruidHiveTimescaleDBUniData,UniVerseVertica infoOpenText™ Vertica™
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