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DBMS > Apache Impala vs. HarperDB vs. Sadas Engine vs. Spark SQL

System Properties Comparison Apache Impala vs. HarperDB vs. Sadas Engine vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHarperDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgwww.harperdb.iowww.sadasengine.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldocs.harperdb.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHarperDBSADAS s.r.l.Apache Software Foundation
Initial release2013201720062014
Current release4.1.0, June 20223.1, August 20218.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community edition availablecommercial infofree trial version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Node.jsC++Scala
Server operating systemsLinuxLinux
OS X
AIX
Linux
Windows
Linux
OS X
Windows
Data schemeyesdynamic schemayesyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes
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
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like data manipulation statementsyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceCustom Functions infosince release 3.1nono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterhorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infothe nodes on which a table resides can be definednonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standardno

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More resources
Apache ImpalaHarperDBSadas EngineSpark SQL
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