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DBMS > Apache Impala vs. Firebolt vs. Microsoft SQL Server vs. Riak TS

System Properties Comparison Apache Impala vs. Firebolt vs. Microsoft SQL Server vs. Riak TS

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFirebolt  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonRiak TS  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseMicrosofts flagship relational DBMSRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.49
Rank#148  Overall
#68  Relational DBMS
Score807.76
Rank#3  Overall
#3  Relational DBMS
Score0.17
Rank#318  Overall
#27  Time Series DBMS
Websiteimpala.apache.orgwww.firebolt.iowww.microsoft.com/­en-us/­sql-server
Technical documentationimpala.apache.org/­impala-docs.htmldocs.firebolt.iolearn.microsoft.com/­en-US/­sql/­sql-serverwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFirebolt Analytics Inc.MicrosoftOpen Source, formerly Basho Technologies
Initial release2013202019892015
Current release4.1.0, June 2022SQL Server 2022, November 20223.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial inforestricted free version is availableOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageC++C++Erlang
Server operating systemsLinuxhostedLinux
Windows
Linux
OS X
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.noyesno
Secondary indexesyesyesyesrestricted
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesyes, limited
APIs and other access methodsJDBC
ODBC
.Net
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
HTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBCGo
JavaScript (Node.js)
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) JavaErlang
Triggersnonoyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingtables can be distributed across several files (horizontal partitioning); sharding through federationSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factordepending on storage layeryes, but depending on the SQL-Server Editionselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardno

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More resources
Apache ImpalaFireboltMicrosoft SQL ServerRiak TS
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