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DBMS > Hypertable vs. Microsoft Azure Data Explorer vs. QuestDB vs. Tarantool vs. Valentina Server

System Properties Comparison Hypertable vs. Microsoft Azure Data Explorer vs. QuestDB vs. Tarantool vs. Valentina Server

Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQuestDB  Xexclude from comparisonTarantool  Xexclude from comparisonValentina Server  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopFully managed big data interactive analytics platformA high performance open source SQL database for time series dataIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsObject-relational database and reports server
Primary database modelWide column storeRelational DBMS infocolumn orientedTime Series DBMSDocument store
Key-value store
Relational DBMS
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
Relational DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerquestdb.iowww.tarantool.iowww.valentina-db.net
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerquestdb.io/­docswww.tarantool.io/­en/­docvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperHypertable Inc.MicrosoftQuestDB Technology IncVKParadigma Software
Initial release20092019201420081999
Current release0.9.8.11, March 2016cloud service with continuous releases2.10.0, May 20225.7.5
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
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.
Implementation languageC++Java (Zero-GC), C++, RustC and C++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
hostedLinux
macOS
Windows
BSD
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yes infoschema-free via InfluxDB Line ProtocolFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or datenoyes 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, datetimeyes
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.yesnono
Secondary indexesrestricted infoonly exact value or prefix value scansall fields are automatically indexednoyesyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL with time-series extensionsFull-featured ANSI SQL supportyes
APIs and other access methodsC++ API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Open binary protocolODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RnoLua, C and SQL stored proceduresyes
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning (by timestamps)Sharding, 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 nodesselectable replication factor on file system levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with eventual consistencyAsynchronous 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 methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 datanonoACID for single-table writesACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infothrough memory mapped filesyes, full featured in-memory storage engine with persistenceyes
User concepts infoAccess controlnoAzure Active Directory AuthenticationAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard
More information provided by the system vendor
HypertableMicrosoft Azure Data ExplorerQuestDBTarantoolValentina Server
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
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