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DBMS > Apache Impala vs. DolphinDB vs. FatDB vs. Infobright vs. Spark SQL

System Properties Comparison Apache Impala vs. DolphinDB vs. FatDB vs. Infobright vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDolphinDB  Xexclude from comparisonFatDB  Xexclude from comparisonInfobright  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAnalytic DBMS for HadoopDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A .NET NoSQL DBMS that can integrate with and extend SQL Server.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSDocument store
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score1.02
Rank#192  Overall
#90  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgwww.dolphindb.comignitetech.com/­softwarelibrary/­infobrightdbspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldocs.dolphindb.cn/­en/­help200/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDolphinDB, IncFatCloudIgnite Technologies Inc.; formerly InfoBright Inc.Apache Software Foundation
Initial release20132018201220052014
Current release4.1.0, June 2022v2.00.4, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community version availablecommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C#CScala
Server operating systemsLinuxLinux
Windows
WindowsLinux
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 infoKnowledge Grid Technology used insteadno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageno infoVia inetgration in SQL ServeryesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyes infovia applicationsnono
Triggersnonoyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesselectable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDno
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.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAdministrators, Users, Groupsno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesno

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More resources
Apache ImpalaDolphinDBFatDBInfobrightSpark SQL
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