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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. H2 vs. RRDtool

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. H2 vs. RRDtool

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonH2  Xexclude from comparisonRRDtool  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 PlatformFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.
Primary database modelRelational DBMSDocument storeRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score8.22
Rank#50  Overall
#32  Relational DBMS
Score2.14
Rank#124  Overall
#10  Time Series DBMS
Websitephoenix.apache.orgcloud.google.com/­datastorewww.h2database.comoss.oetiker.ch/­rrdtool
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docswww.h2database.com/­html/­main.htmloss.oetiker.ch/­rrdtool/­doc
DeveloperApache Software FoundationGoogleThomas MuellerTobias Oetiker
Initial release2014200820051999
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.2.220, July 20231.8.0, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoGPL V2 and FLOSS
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC infoImplementations in Java (e.g. RRD4J) and C# available
Server operating systemsLinux
Unix
Windows
hostedAll OS with a Java VMHP-UX
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesNumeric data only
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 infoExporting into and restoring from XML files possible
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesSQL-like query language (GQL)yesno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
in-process shared library
Pipes
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaC infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsusing Google App EngineJava Stored Procedures and User-Defined Functionsno
TriggersnoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosWith clustering: 2 database servers on different computers operate on identical copies of a databasenone
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 Consistencynone
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 TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes infoby using the rrdcached daemon
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.yesnoyesyes
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-standardno

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Apache PhoenixGoogle Cloud DatastoreH2RRDtool
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