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DBMS > Databricks vs. GridDB vs. QuestDB vs. SiteWhere

System Properties Comparison Databricks vs. GridDB vs. QuestDB vs. SiteWhere

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridDB  Xexclude from comparisonQuestDB  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionThe 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.Scalable in-memory time series database optimized for IoT and Big DataA high performance open source SQL database for time series dataM2M integration platform for persisting/querying time series data
Primary database modelDocument store
Relational DBMS
Time Series DBMSTime Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitewww.databricks.comgriddb.netquestdb.iogithub.com/­sitewhere/­sitewhere
Technical documentationdocs.databricks.comdocs.griddb.netquestdb.io/­docssitewhere1.sitewhere.io/­index.html
DeveloperDatabricksToshiba CorporationQuestDB Technology IncSiteWhere
Initial release2013201320142010
Current release5.1, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java (Zero-GC), C++, RustJava
Server operating systemshostedLinuxLinux
macOS
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes infoschema-free via InfluxDB Line Protocolpredefined scheme
Typing infopredefined data types such as float or dateyes 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.yesnonono
Secondary indexesyesyesnono
SQL infoSupport of SQLwith Databricks SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL with time-series extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
HTTP REST
Supported programming languagesPython
R
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)Sharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationSource-replica replication with eventual consistencyselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID for single-table writesno
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.noyesyes infothrough memory mapped filesno
User concepts infoAccess controlAccess rights for users can be defined per databaseUsers with fine-grained authorization concept
More information provided by the system vendor
DatabricksGridDBQuestDBSiteWhere
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
DatabricksGridDBQuestDBSiteWhere
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