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DBMS > Apache Druid vs. Apache Impala vs. Fujitsu Enterprise Postgres vs. GeoSpock vs. SwayDB

System Properties Comparison Apache Druid vs. Apache Impala vs. Fujitsu Enterprise Postgres vs. GeoSpock vs. SwayDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGeoSpock  Xexclude from comparisonSwayDB  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 dataAnalytic DBMS for HadoopEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Spatial and temporal data processing engine for extreme data scaleAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument storeDocument store
Spatial DBMS
Time 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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitedruid.apache.orgimpala.apache.orgwww.postgresql.fastware.comgeospock.comswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmlwww.postgresql.fastware.com/­product-manuals
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGeoSpockSimer Plaha
Initial release201220132018
Current release29.0.1, April 20244.1.0, June 2022Fujitsu Enterprise Postgres 14, January 20222.0, September 2019
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2commercialcommercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++CJava, JavascriptScala
Server operating systemsLinux
OS X
Unix
LinuxLinux
Windows
hosted
Data schemeyes infoschema-less columns are supportedyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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 indexesyesyesyestemporal, categoricalno
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsyesANSI SQL for query only (using Presto)no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functionsnono
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingpartitioning by range, list and by hashAutomatic shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
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 infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights for users can be defined per tableno
More information provided by the system vendor
Apache DruidApache ImpalaFujitsu Enterprise PostgresGeoSpockSwayDB
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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Apache DruidApache ImpalaFujitsu Enterprise PostgresGeoSpockSwayDB
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