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DBMS > Apache Phoenix vs. Databricks vs. HugeGraph

System Properties Comparison Apache Phoenix vs. Databricks vs. HugeGraph

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonHugeGraph  Xexclude from comparison
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.A fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMSDocument store
Relational DBMS
Graph 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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitephoenix.apache.orgwww.databricks.comgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationphoenix.apache.orgdocs.databricks.comhugegraph.apache.org/­docs
DeveloperApache Software FoundationDatabricksBaidu
Initial release201420132018
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.9
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsLinux
Unix
Windows
hostedLinux
macOS
Unix
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyes
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.noyesno
Secondary indexesyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLyeswith Databricks SQLno
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
Groovy
Java
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregatesasynchronous Gremlin script jobs
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationvia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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-tenancyUsers, roles and permissions
More information provided by the system vendor
Apache PhoenixDatabricksHugeGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache PhoenixDatabricksHugeGraph
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