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DBMS > Apache Druid vs. Apache Impala vs. GridDB vs. IBM Db2 Event Store vs. Microsoft SQL Server

System Properties Comparison Apache Druid vs. Apache Impala vs. GridDB vs. IBM Db2 Event Store vs. Microsoft SQL Server

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataDistributed Event Store optimized for Internet of Things use casesMicrosofts flagship relational DBMS
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSEvent Store
Time Series DBMS
Relational DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
Document store
Graph DBMS
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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score824.29
Rank#3  Overall
#3  Relational DBMS
Websitedruid.apache.orgimpala.apache.orggriddb.netwww.ibm.com/­products/­db2-event-storewww.microsoft.com/­en-us/­sql-server
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmldocs.griddb.netwww.ibm.com/­docs/­en/­db2-event-storelearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationIBMMicrosoft
Initial release20122013201320171989
Current release29.0.1, April 20244.1.0, June 20225.1, August 20222.0SQL Server 2022, November 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree developer edition availablecommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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Implementation languageJavaC++C++C and C++C++
Server operating systemsLinux
OS X
Unix
LinuxLinuxLinux infoLinux, macOS, Windows for the developer additionLinux
Windows
Data schemeyes infoschema-less columns are supportedyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nonononoyes
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)yes infothrough the embedded Spark runtimeyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenoyesTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Java
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingShardingtables can be distributed across several files (horizontal partitioning); sharding through federation
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorSource-replica replicationActive-active shard replicationyes, but depending on the SQL-Server Edition
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency within container, eventual consistency across containersEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
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 KerberosAccess rights for users can be defined per databasefine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidApache ImpalaGridDBIBM Db2 Event StoreMicrosoft SQL Server
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Apache DruidApache ImpalaGridDBIBM Db2 Event StoreMicrosoft SQL Server
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