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DBMS > Apache Impala vs. Dgraph vs. Rockset vs. Spark SQL

System Properties Comparison Apache Impala vs. Dgraph vs. Rockset vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDgraph  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDistributed and scalable native Graph DBMSA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSGraph DBMSDocument storeRelational DBMS
Secondary database modelsDocument storeRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgdgraph.iorockset.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldgraph.io/­docsdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDgraph Labs, Inc.RocksetApache Software Foundation
Initial release2013201620192014
Current release4.1.0, June 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoC++Scala
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesdynamic typingyes
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.nonono infoingestion from XML files supportedno
Secondary indexesyesyesall fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
HTTP RESTJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyesAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSynchronous replication via Raftyesnone
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno infoPlanned for future releasesAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
Apache ImpalaDgraphRocksetSpark SQL
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