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DBMS > Apache Druid vs. BaseX vs. GeoSpock vs. Google Cloud Bigtable

System Properties Comparison Apache Druid vs. BaseX vs. GeoSpock vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBaseX  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Spatial and temporal data processing engine for extreme data scaleGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMS
Time Series DBMS
Native XML DBMSRelational DBMSKey-value store
Wide column store
Secondary database modelsTime 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
Score1.73
Rank#142  Overall
#4  Native XML DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitedruid.apache.orgbasex.orggeospock.comcloud.google.com/­bigtable
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.basex.orgcloud.google.com/­bigtable/­docs
DeveloperApache Software Foundation and contributorsBaseX GmbHGeoSpockGoogle
Initial release201220072015
Current release29.0.1, April 202410.7, August 20232.0, September 2019
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoBSD licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava, Javascript
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
hostedhosted
Data schemeyes infoschema-less columns are supportedschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesyesno
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
Secondary indexesyesyestemporal, categoricalno
SQL infoSupport of SQLSQL for queryingnoANSI SQL for query only (using Presto)no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Actionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyes infovia eventsnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanomultiple readers, single writernoAtomic single-row operations
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.nonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemUsers with fine-grained authorization concept on 4 levelsAccess rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache DruidBaseXGeoSpockGoogle Cloud Bigtable
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