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DBMS > Apache Phoenix vs. GeoMesa vs. Google Cloud Bigtable vs. Oracle Berkeley DB vs. Warp 10

System Properties Comparison Apache Phoenix vs. GeoMesa vs. Google Cloud Bigtable vs. Oracle Berkeley DB vs. Warp 10

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGeoMesa  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Widely used in-process key-value storeTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSSpatial DBMSKey-value store
Wide column store
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitephoenix.apache.orgwww.geomesa.orgcloud.google.com/­bigtablewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.warp10.io
Technical documentationphoenix.apache.orgwww.geomesa.org/­documentation/­stable/­user/­index.htmlcloud.google.com/­bigtable/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperApache Software FoundationCCRi and othersGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleSenX
Initial release20142014201519942015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.0.5, February 202418.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache License 2.0commercialOpen Source infocommercial license availableOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemsLinux
Unix
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnonoyes
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.nononoyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLyesnonoyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Jupyter
WebSocket
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsnononoyes infoWarpScript
Triggersnononoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layerShardingnoneSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
depending on storage layerInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistencydepending on storage layerImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesdepending on storage layernoyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyes infodepending on the DBMS used for storageAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache PhoenixGeoMesaGoogle Cloud BigtableOracle Berkeley DBWarp 10
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