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DBMS > Apache Phoenix vs. Google Cloud Bigtable vs. Hawkular Metrics vs. JanusGraph vs. Postgres-XL

System Properties Comparison Apache Phoenix vs. Google Cloud Bigtable vs. Hawkular Metrics vs. JanusGraph vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSGraph DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitephoenix.apache.orgcloud.google.com/­bigtablewww.hawkular.orgjanusgraph.orgwww.postgres-xl.org
Technical documentationphoenix.apache.orgcloud.google.com/­bigtable/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.janusgraph.orgwww.postgres-xl.org/­documentation
DeveloperApache Software FoundationGoogleCommunity supported by Red HatLinux Foundation; originally developed as Titan by Aurelius
Initial release20142015201420172014 infosince 2012, originally named StormDB
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.6.3, February 202310 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X
Windows
Linux
OS X
Unix
Windows
Linux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nonononoyes infoXML type, but no XML query functionality
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLyesnononoyes infodistributed, parallel query execution
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP RESTJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
Clojure
Java
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsnonoyesuser defined functions
Triggersnonoyes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on Cassandrayes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on Cassandrayes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnoyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noUser authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standard

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More resources
Apache PhoenixGoogle Cloud BigtableHawkular MetricsJanusGraph infosuccessor of TitanPostgres-XL
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