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DBMS > Apache Impala vs. EsgynDB vs. Microsoft Azure Data Explorer vs. Riak KV vs. TDSQL for MySQL

System Properties Comparison Apache Impala vs. EsgynDB vs. Microsoft Azure Data Explorer vs. Riak KV vs. TDSQL for MySQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFully managed big data interactive analytics platformDistributed, fault tolerant key-value storeA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score0.85
Rank#207  Overall
#97  Relational DBMS
Websiteimpala.apache.orgwww.esgyn.cnazure.microsoft.com/­services/­data-explorerwww.tencentcloud.com/­products/­dcdb
Technical documentationimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latestwww.tencentcloud.com/­document/­product/­1042
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynMicrosoftOpenSource, formerly Basho TechnologiesTencent
Initial release20132015201920092013
Current release4.1.0, June 2022cloud service with continuous releases3.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache version 2, commercial enterprise editioncommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaErlang
Server operating systemsLinuxLinuxhostedLinux
OS X
hosted
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyes
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.nonoyesnono
Secondary indexesyesyesall fields are automatically indexedrestrictedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesKusto Query Language (KQL), SQL subsetnoyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored ProceduresYes, possible languages: KQL, Python, RErlangyes
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"Automatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication between multi datacentersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
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.nononono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAzure Active Directory Authenticationyes, using Riak SecurityUsers with fine-grained authorization concept

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More resources
Apache ImpalaEsgynDBMicrosoft Azure Data ExplorerRiak KVTDSQL for MySQL
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