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DBMS > Databend vs. Hive vs. Microsoft Azure Data Explorer vs. NuoDB vs. Tarantool

System Properties Comparison Databend vs. Hive vs. Microsoft Azure Data Explorer vs. NuoDB vs. Tarantool

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNuoDB  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexitydata warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformNuoDB is a webscale distributed database that supports SQL and ACID transactionsIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedRelational DBMSDocument store
Key-value store
Relational 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
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.89
Rank#198  Overall
#92  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
hive.apache.orgazure.microsoft.com/­services/­data-explorerwww.3ds.com/­nuodb-distributed-sql-databasewww.tarantool.io
Technical documentationdocs.databend.comcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorerdoc.nuodb.comwww.tarantool.io/­en/­doc
DeveloperDatabend LabsApache Software Foundation infoinitially developed by FacebookMicrosoftDassault Systèmes infooriginally NuoDB, Inc.VK
Initial release20212012201920132008
Current release1.0.59, April 20233.1.3, April 2022cloud service with continuous releases2.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2commercialcommercial infolimited edition freeOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJavaC++C and C++
Server operating systemshosted
Linux
macOS
All OS with a Java VMhostedhosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
BSD
Linux
macOS
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
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-typesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.noyesnono
Secondary indexesnoyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetyesFull-featured ANSI SQL support
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
Open binary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, RJava, SQLLua, C and SQL stored procedures
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud servicedata is dynamically stored/cached on the nodes where it is read/writtenSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoManaged transparently by NuoDBAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACID infotunable commit protocolACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCCyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTemporary tableyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and rolesAzure Active Directory AuthenticationStandard SQL roles/ privileges, Administrative UsersAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
DatabendHiveMicrosoft Azure Data ExplorerNuoDBTarantool
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