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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. HarperDB vs. JaguarDB

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. HarperDB vs. JaguarDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHarperDB  Xexclude from comparisonJaguarDB  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 PlatformUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Performant, highly scalable DBMS for AI and IoT applications
Primary database modelRelational DBMSDocument storeDocument storeKey-value store
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.60
Rank#244  Overall
#38  Document stores
Score0.06
Rank#381  Overall
#59  Key-value stores
#15  Vector DBMS
Websitephoenix.apache.orgcloud.google.com/­datastorewww.harperdb.iowww.jaguardb.com
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsdocs.harperdb.io/­docswww.jaguardb.com/­support.html
DeveloperApache Software FoundationGoogleHarperDBDataJaguar, Inc.
Initial release2014200820172015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1, August 20213.3 July 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree community edition availableOpen Source infoGPL V3.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsC++ infothe server part. Clients available in other languages
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freedynamic schemayes
Typing infopredefined data types such as float or dateyesyes, details hereyes infoJSON data typesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like data manipulation statementsA subset of ANSI SQL is implemented infobut no views, foreign keys, triggers
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsusing Google App EngineCustom Functions infosince release 3.1no
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosyes infothe nodes on which a table resides can be definedMulti-source replication
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
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)Access rights for users and rolesrights management via user accounts

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More resources
Apache PhoenixGoogle Cloud DatastoreHarperDBJaguarDB
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