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DBMS > Apache Impala vs. Cubrid vs. HarperDB vs. Spark SQL

System Properties Comparison Apache Impala vs. Cubrid vs. HarperDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCubrid  Xexclude from comparisonHarperDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPUltra-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.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSDocument storeRelational 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
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgcubrid.com (korean)
cubrid.org (english)
www.harperdb.iospark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlcubrid.org/­manualsdocs.harperdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCUBRID Corporation, CUBRID FoundationHarperDBApache Software Foundation
Initial release2013200820172014
Current release4.1.0, June 202211.0, January 20213.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial infofree community edition 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++C, C++, JavaNode.jsScala
Server operating systemsLinuxLinux
Windows
Linux
OS X
Linux
OS X
Windows
Data schemeyesyesdynamic schemayes
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesyes
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 statementsyesSQL-like data manipulation statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.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
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored ProceduresCustom Functions infosince release 3.1no
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneA table resides as a whole on one (or more) nodes in a clusteryes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes infothe nodes on which a table resides can be definednone
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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights for users and rolesno

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More resources
Apache ImpalaCubridHarperDBSpark SQL
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