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DBMS > Apache Impala vs. Databend vs. Graph Engine vs. MarkLogic

System Properties Comparison Apache Impala vs. Databend vs. Graph Engine vs. MarkLogic

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabend  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMarkLogic  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineOperational and transactional Enterprise NoSQL database
Primary database modelRelational DBMSRelational DBMSGraph DBMS
Key-value store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Websiteimpala.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
www.graphengine.iowww.marklogic.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databend.comwww.graphengine.io/­docs/­manualdocs.marklogic.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabend LabsMicrosoftMarkLogic Corp.
Initial release2013202120102001
Current release4.1.0, June 20221.0.59, April 202311.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoMIT Licensecommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Rust.NET and CC++
Server operating systemsLinuxhosted
Linux
macOS
.NETLinux
OS X
Windows
Data schemeyesyesyesschema-free infoSchema can be enforced
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.nononoyes
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes infoSQL92
APIs and other access methodsJDBC
ODBC
CLI Client
JDBC
RESTful HTTP API
RESTful HTTP APIJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
F#
Visual Basic
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesyes infovia XQuery or JavaScript
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization concept, user rolesRole-based access control at the document and subdocument levels

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More resources
Apache ImpalaDatabendGraph Engine infoformer name: TrinityMarkLogic
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