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DBMS > Apache Phoenix vs. Brytlyt vs. Databricks vs. HEAVY.AI vs. Microsoft Azure AI Search

System Properties Comparison Apache Phoenix vs. Brytlyt vs. Databricks vs. HEAVY.AI vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBrytlyt  Xexclude from comparisonDatabricks  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLThe 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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareSearch-as-a-service for web and mobile app development
Primary database modelRelational DBMSRelational DBMSDocument store
Relational DBMS
Relational DBMSSearch engine
Secondary database modelsSpatial DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websitephoenix.apache.orgbrytlyt.iowww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­en-us/­services/­search
Technical documentationphoenix.apache.orgdocs.brytlyt.iodocs.databricks.comdocs.heavy.ailearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software FoundationBrytlytDatabricksHEAVY.AI, Inc.Microsoft
Initial release20142016201320162015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.0, August 20235.10, January 2022V1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++ and CUDAC++ and CUDA
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
hostedLinuxhosted
Data schemeyes infolate-bound, schema-on-read capabilitiesyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.yesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesyeswith Databricks SQLyesno
APIs and other access methodsJDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Python
R
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functions infoin PL/pgSQLuser defined functions and aggregatesnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyesMulti-source replicationyes infoImplicit feature of the cloud service
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
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.yesnoyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes infousing Azure authentication
More information provided by the system vendor
Apache PhoenixBrytlytDatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure AI Search
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache PhoenixBrytlytDatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure AI Search
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