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DBMS > Atos Standard Common Repository vs. Databricks vs. PouchDB vs. QuestDB vs. SiteWhere

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. PouchDB vs. QuestDB vs. SiteWhere

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonPouchDB  Xexclude from comparisonQuestDB  Xexclude from comparisonSiteWhere  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksThe 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.JavaScript DBMS with an API inspired by CouchDBA high performance open source SQL database for time series dataM2M integration platform for persisting/querying time series data
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Document storeTime Series DBMSTime Series DBMS
Secondary database modelsRelational 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
Score2.34
Rank#112  Overall
#21  Document stores
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.compouchdb.comquestdb.iogithub.com/­sitewhere/­sitewhere
Technical documentationdocs.databricks.compouchdb.com/­guidesquestdb.io/­docssitewhere1.sitewhere.io/­index.html
DeveloperAtos Convergence CreatorsDatabricksApache Software FoundationQuestDB Technology IncSiteWhere
Initial release20162013201220142010
Current release17037.1.1, June 2019
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoApache 2.0Open Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScriptJava (Zero-GC), C++, RustJava
Server operating systemsLinuxhostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
macOS
Windows
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-freeyes infoschema-free via InfluxDB Line Protocolpredefined scheme
Typing infopredefined data types such as float or dateoptionalnoyesyes
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.yesyesnonono
Secondary indexesyesyesyes infovia viewsnono
SQL infoSupport of SQLnowith Databricks SQLnoSQL with time-series extensionsno
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
HTTP REST
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
JavaScriptC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnouser defined functions and aggregatesView functions in JavaScriptno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding infowith a proxy-based framework, named couchdb-loungehorizontal partitioning (by timestamps)Sharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Source-replica replication with eventual consistencyselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnoACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes infothrough memory mapped filesno
User concepts infoAccess controlLDAP bind authenticationnoUsers with fine-grained authorization concept
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksPouchDBQuestDBSiteWhere
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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