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DBMS > Apache Impala vs. Google Cloud Bigtable vs. mSQL vs. OrigoDB vs. Prometheus

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. mSQL vs. OrigoDB vs. Prometheus

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonOrigoDB  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.mSQL (Mini SQL) is a simple and lightweight RDBMSA fully ACID in-memory object graph databaseOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSDocument store
Object oriented DBMS
Time Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score1.67
Rank#151  Overall
#70  Relational DBMS
Score0.03
Rank#378  Overall
#51  Document stores
#18  Object oriented DBMS
Score7.92
Rank#51  Overall
#2  Time Series DBMS
Websiteimpala.apache.orgcloud.google.com/­bigtablehughestech.com.au/­products/­msqlorigodb.comprometheus.io
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docsorigodb.com/­docsprometheus.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleHughes TechnologiesRobert Friberg et al
Initial release2013201519942009 infounder the name LiveDB2015
Current release4.1.0, June 20224.4, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree licenses can be providedOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC#Go
Server operating systemsLinuxhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Windows
Linux
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesUser defined using .NET types and collectionsNumeric 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 infocan be achieved using .NETno infoImport of XML data possible
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnono
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
.NET Client API
HTTP API
LINQ
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
.Net.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyesno
Triggersnononoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning infoclient side managed; servers are not synchronizedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesnoneSource-replica replicationyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)nonenone
Foreign keys infoReferential integritynononodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesno
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)noRole based authorizationno

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More resources
Apache ImpalaGoogle Cloud BigtablemSQL infoMini SQLOrigoDBPrometheus
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