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DBMS > Apache Druid vs. Hypertable vs. Kinetica vs. Prometheus vs. Sqrrl

System Properties Comparison Apache Druid vs. Hypertable vs. Kinetica vs. Prometheus vs. Sqrrl

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHypertable  Xexclude from comparisonKinetica  Xexclude from comparisonPrometheus  Xexclude from comparisonSqrrl  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn open source BigTable implementation based on distributed file systems such as HadoopFully vectorized database across both GPUs and CPUsOpen-source Time Series DBMS and monitoring systemAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMS
Time Series DBMS
Wide column storeRelational DBMSTime Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Websitedruid.apache.orgwww.kinetica.comprometheus.iosqrrl.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.kinetica.comprometheus.io/­docs
DeveloperApache Software Foundation and contributorsHypertable Inc.KineticaAmazon infooriginally Sqrrl Data, Inc.
Initial release20122009201220152012
Current release29.0.1, April 20240.9.8.11, March 20167.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoGNU version 3. Commercial license availablecommercialOpen Source infoApache 2.0commercial
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 languageJavaC++C, C++GoJava
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows infoan inofficial Windows port is available
LinuxLinux
Windows
Linux
Data schemeyes infoschema-less columns are supportedschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesNumeric data onlyyes
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.nonono infoImport of XML data possible
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesnoyes
SQL infoSupport of SQLSQL for queryingnoSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
C++ API
Thrift
JDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnonouser defined functionsnono
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factor on file system levelSource-replica replicationyes infoby Federationselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoAtomic updates per row, document, or graph entity
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.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights for users and roles on table levelnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache DruidHypertableKineticaPrometheusSqrrl
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