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DBMS > Apache Phoenix vs. Drizzle vs. EXASOL vs. Google Cloud Bigtable vs. Realm

System Properties Comparison Apache Phoenix vs. Drizzle vs. EXASOL vs. Google Cloud Bigtable vs. Realm

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDrizzle  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRealm  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.High-performance, in-memory, MPP database specifically designed for in-memory analytics.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 DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Wide column store
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score7.41
Rank#52  Overall
#8  Document stores
Websitephoenix.apache.orgwww.exasol.comcloud.google.com/­bigtablerealm.io
Technical documentationphoenix.apache.orgwww.exasol.com/­resourcescloud.google.com/­bigtable/­docsrealm.io/­docs
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerExasolGoogleRealm, acquired by MongoDB in May 2019
Initial release20142008200020152014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.2.4, September 2012
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
OS X
hostedAndroid
Backend: server-less
iOS
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsyesnono
APIs and other access methodsJDBCJDBC.Net
JDBC
ODBC
WebSocket
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++
Java
PHP
Java
Lua
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresuser defined functionsnouser defined functionsnono inforuns within the applications so server-side scripts are unnecessary
Triggersnono infohooks for callbacks inside the server can be used.yesnoyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infoHadoop integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operationsACID
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.yesyesnoyes infoIn-Memory realm
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes

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More resources
Apache PhoenixDrizzleEXASOLGoogle Cloud BigtableRealm
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