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DBMS > Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. RRDtool vs. Teradata Aster

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. RRDtool vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRRDtool  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerIndustry 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.Platform for big data analytics on multistructured data sources and types
Primary database modelDocument storeRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­services/­synapse-analyticsoss.oetiker.ch/­rrdtool
Technical documentationcloud.google.com/­datastore/­docsdocs.microsoft.com/­azure/­synapse-analyticsoss.oetiker.ch/­rrdtool/­doc
DeveloperGoogleMicrosoftTobias OetikerTeradata
Initial release2008201619992005
Current release1.8.0, 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL V2 and FLOSScommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C infoImplementations in Java (e.g. RRD4J) and C# available
Server operating systemshostedhostedHP-UX
Linux
Linux
Data schemeschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyes, details hereyesNumeric 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 possibleyes infoin Aster File Store
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)yesnoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
in-process shared library
Pipes
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
PHP
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
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresusing Google App EngineTransact SQLnoR packages
TriggersCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyes infoSQL Map-Reduce Framework
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 ConsistencynoneImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoby using the rrdcached daemonyes
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesnofine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRRDtoolTeradata Aster
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