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DBMS > Apache Phoenix vs. Dgraph vs. Faircom DB vs. Google Cloud Bigtable

System Properties Comparison Apache Phoenix vs. Dgraph vs. Faircom DB vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDgraph  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed and scalable native Graph DBMSNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSGraph DBMSKey-value store
Relational DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websitephoenix.apache.orgdgraph.iowww.faircom.com/­products/­faircom-dbcloud.google.com/­bigtable
Technical documentationphoenix.apache.orgdgraph.io/­docsdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­bigtable/­docs
DeveloperApache Software FoundationDgraph Labs, Inc.FairCom CorporationGoogle
Initial release2014201619792015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoANSI C, C++
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hosted
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema free, schema optional, schema required, partial schema,schema-free
Typing infopredefined data types such as float or dateyesyesyes, ANSI SQL Types, JSON, typed binary structuresno
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 indexesyesyesyesno
SQL infoSupport of SQLyesnoyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsJDBCGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsnoyes info.Net, JavaScript, C/C++no
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Synchronous replication via Raftyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Internal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDtunable from ACID to Eventually ConsistentAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyno infoPlanned for future releasesFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache PhoenixDgraphFaircom DB infoformerly c-treeACEGoogle Cloud Bigtable
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