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DBMS > Apache Druid vs. etcd vs. GridGain vs. Kinetica vs. Netezza

System Properties Comparison Apache Druid vs. etcd vs. GridGain vs. Kinetica vs. Netezza

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonetcd  Xexclude from comparisonGridGain  Xexclude from comparisonKinetica  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA distributed reliable key-value storeGridGain is an in-memory computing platform, built on Apache IgniteFully vectorized database across both GPUs and CPUsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeKey-value store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial 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
Score7.25
Rank#54  Overall
#5  Key-value stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitedruid.apache.orgetcd.io
github.com/­etcd-io/­etcd
www.gridgain.comwww.kinetica.comwww.ibm.com/­products/­netezza
Technical documentationdruid.apache.org/­docs/­latest/­designetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.gridgain.com/­docs/­index.htmldocs.kinetica.com
DeveloperApache Software Foundation and contributorsGridGain Systems, Inc.KineticaIBM
Initial release2012200720122000
Current release29.0.1, April 20243.4, August 2019GridGain 8.5.17.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJava, C++, .NetC, C++
Server operating systemsLinux
OS X
Unix
FreeBSD
Linux
Windows infoexperimental
Linux
OS X
Solaris
Windows
LinuxLinux infoincluded in appliance
Data schemeyes infoschema-less columns are supportedschema-freeyesyesyes
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.nonoyesno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL for queryingnoANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC
JSON over HTTP
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)user defined functionsyes
Triggersnoyes, watching key changesyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes (replicated cache)Source-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)noyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoACID
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.nonoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoSecurity Hooks for custom implementationsAccess rights for users and roles on table levelUsers with fine-grained authorization concept

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More resources
Apache DruidetcdGridGainKineticaNetezza infoAlso called PureData System for Analytics by IBM
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