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DBMS > Apache Druid vs. Google Cloud Spanner vs. Hypertable vs. Postgres-XL

System Properties Comparison Apache Druid vs. Google Cloud Spanner vs. Hypertable vs. Postgres-XL

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHypertable  Xexclude from comparisonPostgres-XL  Xexclude from comparison
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 dataA 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.An open source BigTable implementation based on distributed file systems such as HadoopBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSWide column storeRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitedruid.apache.orgcloud.google.com/­spannerwww.postgres-xl.org
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­spanner/­docswww.postgres-xl.org/­documentation
DeveloperApache Software Foundation and contributorsGoogleHypertable Inc.
Initial release2012201720092014 infosince 2012, originally named StormDB
Current release29.0.1, April 20240.9.8.11, March 201610 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoMozilla public license
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
hostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Data schemeyes infoschema-less columns are supportedyesschema-freeyes
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.nonoyes infoXML type, but no XML query functionality
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLSQL for queryingyes infoQuery statements complying to ANSI 2011noyes infodistributed, parallel query execution
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
C++ API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnononouser defined functions
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardinghorizontal partitioning
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.selectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationnoACID infoMVCC
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 systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Apache DruidGoogle Cloud SpannerHypertablePostgres-XL
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