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DBMS > 4D vs. Apache Impala vs. Datastax Enterprise vs. Spark SQL

System Properties Comparison 4D vs. Apache Impala vs. Datastax Enterprise vs. Spark SQL

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonApache Impala  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemAnalytic DBMS for HadoopDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSWide column storeRelational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score5.93
Rank#56  Overall
#4  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.4d.comimpala.apache.orgwww.datastax.com/­products/­datastax-enterprisespark.apache.org/­sql
Technical documentationdeveloper.4d.comimpala.apache.org/­impala-docs.htmldocs.datastax.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncApache Software Foundation infoApache top-level project, originally developed by ClouderaDataStaxApache Software Foundation
Initial release1984201320112014
Current releasev20, April 20234.1.0, June 20226.8, April 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen 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++JavaScala
Server operating systemsOS X
Windows
LinuxLinux
OS X
Linux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like DML and DDL statementsSQL-like DML and DDL statements (CQL); Spark SQLSQL-like DML and DDL statements
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
ODBC
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
JDBC
ODBC
Supported programming languages4D proprietary IDE
PHP
All languages supporting JDBC/ODBCC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenono
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factorconfigurable replication factor, datacenter aware, advanced replication for edge computingnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infoAtomicity and isolation are supported for single operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlUsers and groupsAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per objectno
More information provided by the system vendor
4D infoformer name: 4th DimensionApache ImpalaDatastax EnterpriseSpark SQL
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
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Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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4D infoformer name: 4th DimensionApache ImpalaDatastax EnterpriseSpark SQL
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