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DBMS > Amazon DocumentDB vs. Databricks vs. FoundationDB vs. Hawkular Metrics vs. Postgres-XL

System Properties Comparison Amazon DocumentDB vs. Databricks vs. FoundationDB vs. Hawkular Metrics vs. Postgres-XL

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatabricks  Xexclude from comparisonFoundationDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPostgres-XL  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceThe 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.Ordered key-value store. Core features are complimented by layers.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument storeDocument store
Relational DBMS
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.databricks.comgithub.com/­apple/­foundationdbwww.hawkular.orgwww.postgres-xl.org
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.databricks.comapple.github.io/­foundationdbwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.postgres-xl.org/­documentation
DeveloperDatabricksFoundationDBCommunity supported by Red Hat
Initial release20192013201320142014 infosince 2012, originally named StormDB
Current release6.2.28, November 202010 R1, October 2018
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC
Server operating systemshostedhostedLinux
OS X
Windows
Linux
OS X
Windows
Linux
macOS
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free infosome layers support schemasschema-freeyes
Typing infopredefined data types such as float or dateyesno infosome layers support typingyesyes
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.noyesnoyes infoXML type, but no XML query functionality
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLnowith Databricks SQLsupported in specific SQL layer onlynoyes infodistributed, parallel query execution
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP API
HTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Python
R
Scala
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Go
Java
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnouser defined functions and aggregatesin SQL-layer onlynouser defined functions
Triggersnonoyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infobased on Cassandrahorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesyesselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyLinearizable consistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblein SQL-layer onlynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDnoACID infoMVCC
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.nonono
User concepts infoAccess controlAccess rights for users and rolesnonofine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon DocumentDBDatabricksFoundationDBHawkular MetricsPostgres-XL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon DocumentDBDatabricksFoundationDBHawkular MetricsPostgres-XL
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