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DBMS > Apache Druid vs. Google Cloud Datastore vs. Kyligence Enterprise vs. Postgres-XL

System Properties Comparison Apache Druid vs. Google Cloud Datastore vs. Kyligence Enterprise vs. Postgres-XL

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed analytics engine for big data, built on top of Apache KylinBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMS
Time Series DBMS
Document storeRelational DBMSRelational 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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.40
Rank#269  Overall
#124  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitedruid.apache.orgcloud.google.com/­datastorekyligence.io/­kyligence-enterprisewww.postgres-xl.org
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docswww.postgres-xl.org/­documentation
DeveloperApache Software Foundation and contributorsGoogleKyligence, Inc.
Initial release2012200820162014 infosince 2012, originally named StormDB
Current release29.0.1, April 202410 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen 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 languageJavaJavaC
Server operating systemsLinux
OS X
Unix
hostedLinuxLinux
macOS
Data schemeyes infoschema-less columns are supportedschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nononoyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingSQL-like query language (GQL)ANSI SQL for queries (using Apache Calcite)yes infodistributed, parallel query execution
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnousing Google App Engineuser defined functions
TriggersnoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using Paxos
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 Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID 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.nononono
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)fine grained access rights according to SQL-standard

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More resources
Apache DruidGoogle Cloud DatastoreKyligence EnterprisePostgres-XL
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