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DBMS > Apache Impala vs. Google Cloud Spanner vs. Microsoft Azure SQL Database vs. NSDb vs. OrigoDB

System Properties Comparison Apache Impala vs. Google Cloud Spanner vs. Microsoft Azure SQL Database vs. NSDb vs. OrigoDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonNSDb  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Database as a Service offering with high compatibility to Microsoft SQL ServerScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA fully ACID in-memory object graph database
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMSDocument store
Object oriented DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Websiteimpala.apache.orgcloud.google.com/­spannerazure.microsoft.com/­en-us/­products/­azure-sql/­databasensdb.ioorigodb.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­spanner/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlnsdb.io/­Architectureorigodb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoftRobert Friberg et al
Initial release20132017201020172009 infounder the name LiveDB
Current release4.1.0, June 2022V12
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache Version 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Java, ScalaC#
Server operating systemsLinuxhostedhostedLinux
macOS
Linux
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes: int, bigint, decimal, stringUser defined using .NET types and collections
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.nonoyesnono infocan be achieved using .NET
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoQuery statements complying to ANSI 2011yesSQL-like query languageno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
ADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
.NET Client API
HTTP API
LINQ
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoTransact SQLnoyes
Triggersnonoyesyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication with 3 replicas for regional instances.yes, with always 3 replicas availableSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesnodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardRole based authorization

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More resources
Apache ImpalaGoogle Cloud SpannerMicrosoft Azure SQL Database infoformerly SQL AzureNSDbOrigoDB
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