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DBMS > Apache Druid vs. Drizzle vs. Hypertable vs. Snowflake

System Properties Comparison Apache Druid vs. Drizzle vs. Hypertable vs. Snowflake

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDrizzle  Xexclude from comparisonHypertable  Xexclude from comparisonSnowflake  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.An open source BigTable implementation based on distributed file systems such as HadoopCloud-based data warehousing service for structured and semi-structured data
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSWide column storeRelational 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
Score121.33
Rank#9  Overall
#6  Relational DBMS
Websitedruid.apache.orgwww.snowflake.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.snowflake.net/­manuals/­index.html
DeveloperApache Software Foundation and contributorsDrizzle project, originally started by Brian AkerHypertable Inc.Snowflake Computing Inc.
Initial release2012200820092014
Current release29.0.1, April 20247.2.4, September 20120.9.8.11, March 2016
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoGNU GPLOpen Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsLinux
OS X
Unix
FreeBSD
Linux
OS X
Linux
OS X
Windows infoan inofficial Windows port is available
hosted
Data schemeyes infoschema-less columns are supportedyesschema-freeyes infosupport of semi-structured data formats (JSON, XML, Avro)
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesrestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLSQL for queryingyes infowith proprietary extensionsnoyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBCC++ API
Thrift
CLI Client
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Java
PHP
C++
Java
Perl
PHP
Python
Ruby
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononouser defined functions
Triggersnono infohooks for callbacks inside the server can be used.nono infosimilar concept for controling cloud resources
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingyes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
selectable replication factor on file system levelyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.nono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemPluggable authentication mechanisms infoe.g. LDAP, HTTPnoUsers with fine-grained authorization concept, user roles and pluggable authentication

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More resources
Apache DruidDrizzleHypertableSnowflake
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