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DBMS > Google Cloud Datastore vs. HarperDB vs. RRDtool vs. Spark SQL

System Properties Comparison Google Cloud Datastore vs. HarperDB vs. RRDtool vs. Spark SQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHarperDB  Xexclude from comparisonRRDtool  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAutomatically 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.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.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeDocument storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.55
Rank#248  Overall
#38  Document stores
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­datastorewww.harperdb.iooss.oetiker.ch/­rrdtoolspark.apache.org/­sql
Technical documentationcloud.google.com/­datastore/­docsdocs.harperdb.io/­docsoss.oetiker.ch/­rrdtool/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleHarperDBTobias OetikerApache Software Foundation
Initial release2008201719992014
Current release3.1, August 20211.8.0, 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoGPL V2 and FLOSSOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsC infoImplementations in Java (e.g. RRD4J) and C# availableScala
Server operating systemshostedLinux
OS X
HP-UX
Linux
Linux
OS X
Windows
Data schemeschema-freedynamic schemayesyes
Typing infopredefined data types such as float or dateyes, details hereyes infoJSON data typesNumeric data onlyyes
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 infoExporting into and restoring from XML files possibleno
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like data manipulation statementsnoSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
in-process shared library
Pipes
JDBC
ODBC
Supported programming languages.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 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
Java
Python
R
Scala
Server-side scripts infoStored proceduresusing Google App EngineCustom Functions infosince release 3.1nono
TriggersCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusternoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infothe nodes on which a table resides can be definednonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoby using the rrdcached daemonyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesnono

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More resources
Google Cloud DatastoreHarperDBRRDtoolSpark SQL
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