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DBMS > Apache Druid vs. EXASOL vs. GeoSpock vs. Google Cloud Spanner

System Properties Comparison Apache Druid vs. EXASOL vs. GeoSpock vs. Google Cloud Spanner

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEXASOL  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Spanner  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 dataHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Spatial and temporal data processing engine for extreme data scaleA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSRelational DBMS
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
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Websitedruid.apache.orgwww.exasol.comgeospock.comcloud.google.com/­spanner
Technical documentationdruid.apache.org/­docs/­latest/­designwww.exasol.com/­resourcescloud.google.com/­spanner/­docs
DeveloperApache Software Foundation and contributorsExasolGeoSpockGoogle
Initial release201220002017
Current release29.0.1, April 20242.0, September 2019
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, Javascript
Server operating systemsLinux
OS X
Unix
hostedhosted
Data schemeyes infoschema-less columns are supportedyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyestemporal, categoricalyes
SQL infoSupport of SQLSQL for queryingyesANSI SQL for query only (using Presto)yes infoQuery statements complying to ANSI 2011
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.Net
JDBC
ODBC
WebSocket
JDBCgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java
Lua
Python
R
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationnoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infoStrict serializable isolation
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.noyesnono
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 according to SQL-standardAccess 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 DruidEXASOLGeoSpockGoogle Cloud Spanner
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