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DBMS > Databricks vs. Microsoft Azure Table Storage vs. QuestDB vs. RDF4J

System Properties Comparison Databricks vs. Microsoft Azure Table Storage vs. QuestDB vs. RDF4J

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonQuestDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  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.A Wide Column Store for rapid development using massive semi-structured datasetsA high performance open source SQL database for time series dataRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument store
Relational DBMS
Wide column storeTime Series DBMSRDF store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.databricks.comazure.microsoft.com/­en-us/­services/­storage/­tablesquestdb.iordf4j.org
Technical documentationdocs.databricks.comquestdb.io/­docsrdf4j.org/­documentation
DeveloperDatabricksMicrosoftQuestDB Technology IncSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2013201220142004
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava (Zero-GC), C++, RustJava
Server operating systemshostedhostedLinux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes infoschema-free via InfluxDB Line Protocolyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes
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.yesnono
Secondary indexesyesnonoyes
SQL infoSupport of SQLwith Databricks SQLnoSQL with time-series extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesPython
R
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning (by timestamps)none
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACID for single-table writesACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infothrough memory mapped files
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesno
More information provided by the system vendor
DatabricksMicrosoft Azure Table StorageQuestDBRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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