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DBMS > Apache Phoenix vs. Databricks vs. DuckDB vs. Sphinx vs. Yanza

System Properties Comparison Apache Phoenix vs. Databricks vs. DuckDB vs. Sphinx vs. Yanza

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonDuckDB  Xexclude from comparisonSphinx  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA 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.An embeddable, in-process, column-oriented SQL OLAP RDBMSOpen source search engine for searching in data from different sources, e.g. relational databasesTime Series DBMS for IoT Applications
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSSearch engineTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.57
Rank#74  Overall
#40  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitephoenix.apache.orgwww.databricks.comduckdb.orgsphinxsearch.comyanza.com
Technical documentationphoenix.apache.orgdocs.databricks.comduckdb.org/­docssphinxsearch.com/­docs
DeveloperApache Software FoundationDatabricksSphinx Technologies Inc.Yanza
Initial release20142013201820012015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.10, February 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMIT LicenseOpen Source infoGPL version 2, commercial licence availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++
Server operating systemsLinux
Unix
Windows
hostedserver-lessFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesnono
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.noyesnono
Secondary indexesyesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLyeswith Databricks SQLyesSQL-like query language (SphinxQL)no
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
Proprietary protocolHTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregatesnonono
Triggersnononoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynonono
More information provided by the system vendor
Apache PhoenixDatabricksDuckDBSphinxYanza
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more

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More resources
Apache PhoenixDatabricksDuckDBSphinxYanza
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