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DBMS > Apache Phoenix vs. BigObject vs. Dgraph vs. GridDB vs. SwayDB

System Properties Comparison Apache Phoenix vs. BigObject vs. Dgraph vs. GridDB vs. SwayDB

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBigObject  Xexclude from comparisonDgraph  Xexclude from comparisonGridDB  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAnalytic DBMS for real-time computations and queriesDistributed and scalable native Graph DBMSScalable in-memory time series database optimized for IoT and Big DataAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedGraph DBMSTime Series DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitephoenix.apache.orgbigobject.iodgraph.iogriddb.netswaydb.simer.au
Technical documentationphoenix.apache.orgdocs.bigobject.iodgraph.io/­docsdocs.griddb.net
DeveloperApache Software FoundationBigObject, Inc.Dgraph Labs, Inc.Toshiba CorporationSimer Plaha
Initial release20142015201620132018
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoC++Scala
Server operating systemsLinux
Unix
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Windows
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.nonononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBCfluentd
ODBC
RESTful HTTP API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Kotlin
Scala
Server-side scripts infoStored proceduresuser defined functionsLuanonono
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneSynchronous replication via RaftSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencynoneImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID at container levelAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes
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.yesyesyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynono infoPlanned for future releasesAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache PhoenixBigObjectDgraphGridDBSwayDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache PhoenixBigObjectDgraphGridDBSwayDB
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