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DBMS > Hive vs. Microsoft Azure Data Explorer vs. Sphinx vs. Splice Machine vs. TiDB

System Properties Comparison Hive vs. Microsoft Azure Data Explorer vs. Sphinx vs. Splice Machine vs. TiDB

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTiDB  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTiDB is an open source distributed SQL database that supports Hybrid Transactional/Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.
Primary database modelRelational DBMSRelational DBMS infocolumn orientedSearch engineRelational DBMSRelational DBMS
Secondary database modelsDocument 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score4.25
Rank#74  Overall
#40  Relational DBMS
Websitehive.apache.orgazure.microsoft.com/­services/­data-explorersphinxsearch.comsplicemachine.compingcap.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docssplicemachine.com/­how-it-worksdocs.pingcap.com/­tidb/­stable
DeveloperApache Software Foundation infoinitially developed by FacebookMicrosoftSphinx Technologies Inc.Splice MachinePingCAP, Inc.
Initial release20122019200120142016
Current release3.1.3, April 2022cloud service with continuous releases3.5.1, February 20233.1, March 20218.1.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
TiDB Cloud: Fully-managed TiDB Service. Bring everything great about TiDB to the cloud.
Implementation languageJavaC++JavaGo, Rust
Server operating systemsAll OS with a Java VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyesyes
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.yesno
Secondary indexesyesall fields are automatically indexedyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)yesyes
APIs and other access methodsJDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
GORM
JDBC
ODBC
Proprietary protocol
SQLAlchemy
Supported programming languagesC++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, Rnoyes infoJavano
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning (by key range)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication
Source-replica replication
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoYes, via Full Spark Integrationyes infowith TiSpark Connector
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes infofull support since version 6.6
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and rolesAzure Active Directory AuthenticationnoAccess rights for users, groups and roles according to SQL-standardFine grained access rights according to SQL-standard
More information provided by the system vendor
HiveMicrosoft Azure Data ExplorerSphinxSplice MachineTiDB
Specific characteristicsTiDB is an advanced open-source, distributed SQL database for modern application...
» more
Competitive advantages- HORIZONTAL SCALING : TiDB grants total transparency into your data workloads without...
» more
Typical application scenariosTiDB is ideal for transactional applications that require extreme scalability and...
» more
Key customersBlock, Pinterest, Catalyst, Bolt, Flipkart, Capcom, Shopee (E-commerce), JD Cloud...
» more
Market metrics34K+ GitHub stars 5K+ members in TiDB Community Slack 1K+ community contributors...
» more
Licensing and pricing modelsTiDB Community : Free open source software (Apache 2.0) TiDB Self-Hosted : Enterprise...
» more

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HiveMicrosoft Azure Data ExplorerSphinxSplice MachineTiDB
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