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DBMS > Apache Druid vs. CouchDB vs. InterSystems Caché vs. Teradata Aster vs. Vertica

System Properties Comparison Apache Druid vs. CouchDB vs. InterSystems Caché vs. Teradata Aster vs. Vertica

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonTeradata Aster  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.A multi-model DBMS and application serverPlatform for big data analytics on multistructured data sources and typesCloud 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
Document storeKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS infousing the Geocouch extensionDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score9.30
Rank#45  Overall
#7  Document stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitedruid.apache.orgcouchdb.apache.orgwww.intersystems.com/­products/­cachewww.vertica.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.couchdb.org/­en/­stabledocs.intersystems.comvertica.com/­documentation
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerInterSystemsTeradataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122005199720052005
Current release29.0.1, April 20243.3.3, December 20232018.1.4, May 202012.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache version 2commercialcommercialcommercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaErlangC++
Server operating systemsLinux
OS X
Unix
Android
BSD
Linux
OS X
Solaris
Windows
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
LinuxLinux
Data schemeyes infoschema-less columns are supportedschema-freedepending on used data modelFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File StoreYes, 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 dateyesnoyesyesyes
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.nonoyesyes infoin Aster File Storeno
Secondary indexesyesyes infovia viewsyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL for queryingnoyesyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP/JSON API.NET Client API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
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
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C#
C++
Java
C
C#
C++
Java
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoView functions in JavaScriptyesR packagesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoimproved architecture with release 2.0noneShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
Source-replica replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Multi-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 methodsnoyesnoyes infoSQL Map-Reduce Frameworkno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single document possibleACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyesyes
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.nonoyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users can be defined per databaseAccess rights for users, groups and rolesfine 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 DruidCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"InterSystems CachéTeradata AsterVertica 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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Apache DruidCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"InterSystems CachéTeradata AsterVertica infoOpenText™ Vertica™
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