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DBMS > Apache Impala vs. Google Cloud Datastore vs. HyperSQL vs. mSQL vs. Prometheus

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. HyperSQL vs. mSQL vs. Prometheus

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBmSQL (Mini SQL) is a simple and lightweight RDBMSOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSTime 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
Score4.49
Rank#79  Overall
#12  Document stores
Score3.90
Rank#85  Overall
#46  Relational DBMS
Score1.67
Rank#151  Overall
#70  Relational DBMS
Score7.92
Rank#51  Overall
#2  Time Series DBMS
Websiteimpala.apache.orgcloud.google.com/­datastorehsqldb.orghughestech.com.au/­products/­msqlprometheus.io
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docshsqldb.org/­web/­hsqlDocsFrame.htmlprometheus.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleHughes Technologies
Initial release20132008200119942015
Current release4.1.0, June 20222.7.2, June 20234.4, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infobased on BSD licensecommercial infofree licenses can be providedOpen 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++JavaCGo
Server operating systemsLinuxhostedAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes, 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.nonononono infoImport of XML data possible
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)yesA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API infoJDBC via HTTP
JDBC
ODBC
JDBC
ODBC
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC
Java
C
C++
Delphi
Java
Perl
PHP
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App EngineJava, SQLnono
TriggersnoCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosnonenoneyes infoby Federation
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 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 Consistencynonenone
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnono
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-standardnono

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More resources
Apache ImpalaGoogle Cloud DatastoreHyperSQL infoalso known as HSQLDBmSQL infoMini SQLPrometheus
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