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DBMS > Apache Phoenix vs. Drizzle vs. Google Cloud Datastore vs. InfinityDB

System Properties Comparison Apache Phoenix vs. Drizzle vs. Google Cloud Datastore vs. InfinityDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfinityDB  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Java embedded Key-Value Store which extends the Java Map interface
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#378  Overall
#57  Key-value stores
Websitephoenix.apache.orgcloud.google.com/­datastoreboilerbay.com
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsboilerbay.com/­infinitydb/­manual
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerGoogleBoiler Bay Inc.
Initial release2014200820082002
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.2.4, September 20124.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
OS X
hostedAll OS with a Java VM
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgrade
Typing infopredefined data types such as float or dateyesyesyes, details hereyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arrays
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.nonono
Secondary indexesyesyesyesno infomanual creation possible, using inversions based on multi-value capability
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL-like query language (GQL)no
APIs and other access methodsJDBCJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Server-side scripts infoStored proceduresuser defined functionsnousing Google App Engineno
Triggersnono infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Multi-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno infomanual creation possible, using inversions based on multi-value capability
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoOptimistic locking for transactions; no isolation for bulk loads
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.yesnono
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 based on Google Cloud Identity and Access Management (IAM)no

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More resources
Apache PhoenixDrizzleGoogle Cloud DatastoreInfinityDB
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