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DBMS > Apache Phoenix vs. Axibase vs. Badger vs. Google Cloud Bigtable vs. HEAVY.AI

System Properties Comparison Apache Phoenix vs. Axibase vs. Badger vs. Google Cloud Bigtable vs. HEAVY.AI

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonAxibase  Xexclude from comparisonBadger  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMSTime Series DBMSKey-value storeKey-value store
Wide column store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score0.32
Rank#288  Overall
#25  Time Series DBMS
Score0.20
Rank#325  Overall
#49  Key-value stores
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score2.10
Rank#126  Overall
#61  Relational DBMS
Websitephoenix.apache.orgaxibase.com/­docs/­atsd/­financegithub.com/­dgraph-io/­badgercloud.google.com/­bigtablegithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationphoenix.apache.orggodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­bigtable/­docsdocs.heavy.ai
DeveloperApache Software FoundationAxibase CorporationDGraph LabsGoogleHEAVY.AI, Inc.
Initial release20142013201720152016
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019155855.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen Source infoApache 2.0commercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGoC++ and CUDA
Server operating systemsLinux
Unix
Windows
LinuxBSD
Linux
OS X
Solaris
Windows
hostedLinux
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoshort, integer, long, float, double, decimal, stringnonoyes
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 indexesyesnononono
SQL infoSupport of SQLyesSQL-like query languagenonoyes
APIs and other access methodsJDBCJDBC
Proprietary protocol (Network API)
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Vega
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
PHP
Python
R
Ruby
GoC#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresuser defined functionsyesnonono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnoneInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencynoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnonoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache PhoenixAxibaseBadgerGoogle Cloud BigtableHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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