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DBMS > Apache Druid vs. Kdb vs. Netezza vs. RavenDB

System Properties Comparison Apache Druid vs. Kdb vs. Netezza vs. RavenDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonKdb  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHigh performance Time Series DBMSData warehouse and analytics appliance part of IBM PureSystemsOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMS
Vector DBMS
Relational DBMSDocument store
Secondary database modelsRelational DBMSGraph DBMS
Spatial 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
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websitedruid.apache.orgkx.comwww.ibm.com/­products/­netezzaravendb.net
Technical documentationdruid.apache.org/­docs/­latest/­designcode.kx.comravendb.net/­docs
DeveloperApache Software Foundation and contributorsKx Systems, a division of First Derivatives plcIBMHibernating Rhinos
Initial release20122000 infokdb was released 2000, kdb+ in 200320002010
Current release29.0.1, April 20243.6, May 20185.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree 32-bit versioncommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaqC#
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
Linux infoincluded in applianceLinux
macOS
Raspberry Pi
Windows
Data schemeyes infoschema-less columns are supportedyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyes infotable attribute 'grouped'yesyes
SQL infoSupport of SQLSQL for queryingSQL-like query language (q)yesSQL-like query language (RQL)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
OLE DB
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsyesyes
Triggersnoyes infowith viewsnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationSource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infosimilar paradigm used for internal processingyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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 systemrights management via user accountsUsers with fine-grained authorization conceptAuthorization levels configured per client per database
More information provided by the system vendor
Apache DruidKdbNetezza infoAlso called PureData System for Analytics by IBMRavenDB
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
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More resources
Apache DruidKdbNetezza infoAlso called PureData System for Analytics by IBMRavenDB
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