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DBMS > Apache IoTDB vs. Databricks vs. GigaSpaces vs. SiriDB vs. Yaacomo

System Properties Comparison Apache IoTDB vs. Databricks vs. GigaSpaces vs. SiriDB vs. Yaacomo

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSiriDB  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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 FlinkThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsOpen Source Time Series DBMSOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelTime Series DBMSDocument store
Relational DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSRelational DBMS
Secondary database modelsGraph DBMS
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DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Websiteiotdb.apache.orgwww.databricks.comwww.gigaspaces.comsiridb.comyaacomo.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comdocs.gigaspaces.com/­latest/­landing.htmldocs.siridb.com
DeveloperApache Software FoundationDatabricksGigaspaces TechnologiesCesbitQ2WEB GmbH
Initial release20182013200020172009
Current release1.1.0, April 202315.5, September 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoMIT Licensecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetC
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
macOS
Solaris
Windows
LinuxAndroid
Linux
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes infoNumeric datayes
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 infoXML can be used for describing objects metadatanono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLSQL-99 for query and DML statementsnoyes
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP APIJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesyesno
Triggersyesyes, event driven architecturenoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infoMap-Reduce pattern can be built with XAP task executorsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
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.yesnoyesyesyes
User concepts infoAccess controlyesRole-based access controlsimple rights management via user accountsfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBDatabricksGigaSpacesSiriDBYaacomo
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache IoTDBDatabricksGigaSpacesSiriDBYaacomo
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