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DBMS > Apache IoTDB vs. GBase vs. IBM Db2 warehouse vs. Microsoft Azure Synapse Analytics vs. Solr

System Properties Comparison Apache IoTDB vs. GBase vs. IBM Db2 warehouse vs. Microsoft Azure Synapse Analytics vs. Solr

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGBase  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Cloud-based data warehousing serviceElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orgwww.gbase.cnwww.ibm.com/­products/­db2/­warehouseazure.microsoft.com/­services/­synapse-analyticssolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­azure/­synapse-analyticssolr.apache.org/­resources.html
DeveloperApache Software FoundationGeneral Data Technology Co., Ltd.IBMMicrosoftApache Software Foundation
Initial release20182004201420162006
Current release1.1.0, April 2023GBase 8a, GBase 8s, GBase 8c9.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, Java, PythonC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxhostedhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyesyes infosupports customizable data types and automatic typing
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.noyesno infoImport/export of XML data possiblenoyes
Secondary indexesyesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageStandard with numerous extensionsyesyesSolr Parallel SQL Interface
APIs and other access methodsJDBC
Native API
ADO.NET
C API
JDBC
ODBC
.NET Client API
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C#
Java
PHP
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesuser defined functionsPL/SQL, SQL PLTransact SQLJava plugins
Triggersyesyesyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesyesyes
User concepts infoAccess controlyesyesfine grained access rights according to SQL-standardyesyes

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More resources
Apache IoTDBGBaseIBM Db2 warehouse infoformerly named IBM dashDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSolr
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