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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. TimescaleDB vs. VelocityDB

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. TimescaleDB vs. VelocityDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVelocityDB  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 time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelRelational DBMSDocument storeTime Series DBMSGraph DBMS
Object oriented DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Score0.00
Rank#385  Overall
#40  Graph DBMS
#21  Object oriented DBMS
Websitephoenix.apache.orgcloud.google.com/­datastorewww.timescale.comvelocitydb.com
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsdocs.timescale.comvelocitydb.com/­UserGuide
DeveloperApache Software FoundationGoogleTimescaleVelocityDB Inc
Initial release2014200820172011
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.15.0, May 20247.x
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercial
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 languageJavaCC#
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X
Windows
Any that supports .NET
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details herenumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex 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.nonoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)yes infofull PostgreSQL SQL syntaxno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
.Net
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
.Net
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
TriggersnoCallbacks using the Google Apps EngineyesCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosSource-replica replication with hot standby and reads on replicas info
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 pathsyesno
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.yesnonoyes
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)fine grained access rights according to SQL-standardBased on Windows Authentication

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More resources
Apache PhoenixGoogle Cloud DatastoreTimescaleDBVelocityDB
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