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DBMS > Apache Impala vs. Google Cloud Datastore vs. HyperSQL vs. Prometheus vs. TDSQL for MySQL

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. HyperSQL vs. Prometheus vs. TDSQL for MySQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonPrometheus  Xexclude from comparisonTDSQL for MySQL  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 HSQLDBOpen-source Time Series DBMS and monitoring systemA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelRelational DBMSDocument storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­datastorehsqldb.orgprometheus.iowww.tencentcloud.com/­products/­dcdb
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docshsqldb.org/­web/­hsqlDocsFrame.htmlprometheus.io/­docswww.tencentcloud.com/­document/­product/­1042
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleTencent
Initial release20132008200120152013
Current release4.1.0, June 20222.7.2, June 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infobased on BSD licenseOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaGo
Server operating systemsLinuxhostedAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesLinux
Windows
hosted
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes, 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.nononono infoImport of XML data possibleno
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)yesnoyes
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API infoJDBC via HTTP
JDBC
ODBC
RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC
Java
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App EngineJava, SQLnoyes
TriggersnoCallbacks using the Google Apps Engineyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosnoneyes infoby FederationMulti-source replication
Source-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 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
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 TransactionsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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-standardnoUsers with fine-grained authorization concept

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More resources
Apache ImpalaGoogle Cloud DatastoreHyperSQL infoalso known as HSQLDBPrometheusTDSQL for MySQL
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