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DBMS > Apache Druid vs. Google Cloud Bigtable vs. Quasardb vs. Tkrzw

System Properties Comparison Apache Druid vs. Google Cloud Bigtable vs. Quasardb vs. Tkrzw

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonQuasardb  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed, high-performance timeseries databaseA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Wide column store
Time Series DBMSKey-value store
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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitedruid.apache.orgcloud.google.com/­bigtablequasar.aidbmx.net/­tkrzw
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­bigtable/­docsdoc.quasar.ai/­master
DeveloperApache Software Foundation and contributorsGooglequasardbMikio Hirabayashi
Initial release2012201520092020
Current release29.0.1, April 20243.14.1, January 20240.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsLinux
OS X
Unix
hostedBSD
Linux
OS X
Windows
Linux
macOS
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyes infointeger and binaryno
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.nononono
Secondary indexesyesnoyes infowith tags
SQL infoSupport of SQLSQL for queryingnoSQL-like query languageno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyeswith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoTransient modeyes infousing specific database classes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cryptographically strong user authentication and audit trailno

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More resources
Apache DruidGoogle Cloud BigtableQuasardbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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