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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. Informix vs. WakandaDB

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. Informix vs. WakandaDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInformix  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSDocument storeRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBObject oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
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
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitephoenix.apache.orgcloud.google.com/­datastorewww.ibm.com/­products/­informixwakanda.github.io
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
wakanda.github.io/­doc
DeveloperApache Software FoundationGoogleIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Wakanda SAS
Initial release2014200819842012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201914.10.FC5, November 20202.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree developer edition availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++ and JavaC++, JavaScript
Server operating systemsLinux
Unix
Windows
hostedAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyes infoSince Version 12.10 support for JSON/BSON datatypesyes
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 indexesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)yesno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineyesyes
TriggersnoCallbacks using the Google Apps Engineyesyes
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 using PaxosMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infousing Google Cloud Dataflownono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
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.yesnoyesno
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)Users with fine-grained authentication, authorization, and auditing controlsyes

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More resources
Apache PhoenixGoogle Cloud DatastoreInformixWakandaDB
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