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DBMS > Apache Phoenix vs. Google Cloud Bigtable vs. Hazelcast vs. Warp 10

System Properties Comparison Apache Phoenix vs. Google Cloud Bigtable vs. Hazelcast vs. Warp 10

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonWarp 10  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.A widely adopted in-memory data gridTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value storeTime Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
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
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitephoenix.apache.orgcloud.google.com/­bigtablehazelcast.comwww.warp10.io
Technical documentationphoenix.apache.orgcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docswww.warp10.io/­content/­02_Getting_started
DeveloperApache Software FoundationGoogleHazelcastSenX
Initial release2014201520082015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsLinux
Unix
Windows
hostedAll OS with a Java VMLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyes infothe object must implement a serialization strategyno
Secondary indexesyesnoyesno
SQL infoSupport of SQLyesnoSQL-like query languageno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP API
Jupyter
WebSocket
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functionsnoyes infoEvent Listeners, Executor Servicesyes infoWarpScript
Triggersnonoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infobased on HBase
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 zonesyes infoReplicated Mapselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesyesno
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)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
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)Role-based access controlMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache PhoenixGoogle Cloud BigtableHazelcastWarp 10
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