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DBMS > Google Cloud Datastore vs. GridGain vs. Interbase vs. RRDtool

System Properties Comparison Google Cloud Datastore vs. GridGain vs. Interbase vs. RRDtool

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonInterbase  Xexclude from comparisonRRDtool  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache IgniteLight-weight proven RDBMS infooriginally from BorlandIndustry 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 modelDocument storeKey-value store
Relational DBMS
Relational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score1.90
Rank#132  Overall
#11  Time Series DBMS
Websitecloud.google.com/­datastorewww.gridgain.comwww.embarcadero.com/­products/­interbaseoss.oetiker.ch/­rrdtool
Technical documentationcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmldocs.embarcadero.com/­products/­interbaseoss.oetiker.ch/­rrdtool/­doc
DeveloperGoogleGridGain Systems, Inc.EmbarcaderoTobias Oetiker
Initial release2008200719841999
Current releaseGridGain 8.5.1InterBase 2020, December 20191.8.0, 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL V2 and FLOSS
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 languageJava, C++, .NetCC infoImplementations in Java (e.g. RRD4J) and C# available
Server operating systemshostedLinux
OS X
Solaris
Windows
Android
iOS
Linux
OS X
Windows
HP-UX
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesNumeric 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.noyesno infoexport as XML data possibleno infoExporting into and restoring from XML files possible
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
in-process shared library
Pipes
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
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
Server-side scripts infoStored proceduresusing Google App Engineyes (compute grid and cache interceptors can be used instead)yes infoInterbase procedure and trigger languageno
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)yesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)Interbase Change Viewsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)nono
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 ConsistencyImmediate Consistencynone
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMultiversion concurreny controlyes 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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsfine grained access rights according to SQL-standardno

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More resources
Google Cloud DatastoreGridGainInterbaseRRDtool
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