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DBMS > Apache Impala vs. HarperDB vs. MarkLogic vs. Memgraph vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Impala vs. HarperDB vs. MarkLogic vs. Memgraph vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHarperDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonMemgraph  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopUltra-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.Operational and transactional Enterprise NoSQL databaseAn open source graph database built for real-time streaming and compatible with Neo4jFully managed big data interactive analytics platform
Primary database modelRelational DBMSDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Graph DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument storeDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score3.19
Rank#94  Overall
#8  Graph DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteimpala.apache.orgwww.harperdb.iowww.progress.com/­marklogicmemgraph.comazure.microsoft.com/­services/­data-explorer
Technical documentationimpala.apache.org/­impala-docs.htmldocs.harperdb.io/­docswww.progress.com/­marklogic/­documentationmemgraph.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
Social network pagesLinkedInTwitterFacebookGitHubDiscord
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHarperDBMarkLogic Corp.Memgraph LtdMicrosoft
Initial release20132017200120172019
Current release4.1.0, June 20223.1, August 202111.0, December 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community edition availablecommercial inforestricted free version is availableOpen Source infoBSL 1.1; commercial license for enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Node.jsC++C and C++
Server operating systemsLinuxLinux
OS X
Linux
OS X
Windows
Linuxhosted
Data schemeyesdynamic schemaschema-free infoSchema can be enforcedschema-free and schema-optionalFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonoyesnoyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like data manipulation statementsyes infoSQL92noKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Bolt protocol
Cypher query language
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.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
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceCustom Functions infosince release 3.1yes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, R
Triggersnonoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingSharding infodynamic graph partitioningSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infothe nodes on which a table resides can be definedyesMulti-source replication using RAFTyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACID infocan act as a resource manager in an XA/JTA transactionACID infowith snapshot isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes, using LMDByesyes infowith periodic snapshot and write-ahead logging (WAL) of changesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and rolesRole-based access control at the document and subdocument levelsUsers, roles and permissionsAzure Active Directory Authentication
More information provided by the system vendor
Apache ImpalaHarperDBMarkLogicMemgraphMicrosoft Azure Data Explorer
Specific characteristicsMemgraph directly connects to your streaming infrastructure so you and your team...
» more
Competitive advantagesBusiness Source License ensures a future for the Memgraph community MAGE algorithm...
» more
Typical application scenariosGraph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more
Licensing and pricing modelsYou can check out our pricing model and licenses on the company website .
» more

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More resources
Apache ImpalaHarperDBMarkLogicMemgraphMicrosoft Azure Data Explorer
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