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DBMS > Amazon DocumentDB vs. Apache Phoenix vs. Databricks vs. OceanBase

System Properties Comparison Amazon DocumentDB vs. Apache Phoenix vs. Databricks vs. OceanBase

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonOceanBase  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA scale-out RDBMS with evolutionary schema built on Apache HBaseThe 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 distributed, high available RDBMS compatible with Oracle and MySQL
Primary database modelDocument storeRelational DBMSDocument store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score1.97
Rank#119  Overall
#58  Relational DBMS
Websiteaws.amazon.com/­documentdbphoenix.apache.orgwww.databricks.comen.oceanbase.com
Technical documentationaws.amazon.com/­documentdb/­resourcesphoenix.apache.orgdocs.databricks.comen.oceanbase.com/­docs/­oceanbase-database
DeveloperApache Software FoundationDatabricksOceanBase infopreviously Alibaba and Ant Group
Initial release2019201420132010
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.3.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoCommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedLinux
Unix
Windows
hostedLinux
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yes
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.nonoyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyeswith Databricks SQLyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
Server-side scripts infoStored proceduresnouser defined functionsuser defined functions and aggregatesPL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning (by hash, key, range, range columns, list, and list columns)
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication
Source-replica replication
yesMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDACID
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.yesno
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Amazon DocumentDBApache PhoenixDatabricksOceanBase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon DocumentDBApache PhoenixDatabricksOceanBase
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