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DBMS > Apache Phoenix vs. Bangdb vs. Geode vs. Microsoft Azure Table Storage

System Properties Comparison Apache Phoenix vs. Bangdb vs. Geode vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBangdb  Xexclude from comparisonGeode  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseConverged and high performance database for device data, events, time series, document and graphGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Key-value storeWide column store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitephoenix.apache.orgbangdb.comgeode.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationphoenix.apache.orgdocs.bangdb.comgeode.apache.org/­docs
DeveloperApache Software FoundationSachin Sinha, BangDBOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Microsoft
Initial release2014201220022012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019BangDB 2.0, October 20211.1, February 2017
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD 3Open Source infoApache Version 2; commercial licenses available as Gemfirecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++Java
Server operating systemsLinux
Unix
Windows
LinuxAll OS with a Java VM infothe JDK (8 or later) is also requiredhosted
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes
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.nononono
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialnono
SQL infoSupport of SQLyesSQL like support with command line toolSQL-like query language (OQL)no
APIs and other access methodsJDBCProprietary protocol
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
Python
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnouser defined functionsno
Triggersnoyes, Notifications (with Streaming only)yes infoCache Event Listenersno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor, Knob for CAP (enterprise version only)Multi-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyTunable consistency, set CAP knob accordinglyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes, on a single nodeoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only modeyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyes (enterprise version only)Access rights per client and object definableAccess rights based on private key authentication or shared access signatures

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More resources
Apache PhoenixBangdbGeodeMicrosoft Azure Table Storage
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