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DBMS > AlaSQL vs. HEAVY.AI vs. Manticore Search vs. Microsoft Azure Data Explorer vs. Riak TS

System Properties Comparison AlaSQL vs. HEAVY.AI vs. Manticore Search vs. Microsoft Azure Data Explorer vs. Riak TS

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak TS  Xexclude from comparison
DescriptionJavaScript DBMS libraryA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareMulti-storage database for search, including full-text search.Fully managed big data interactive analytics platformRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelDocument store
Relational DBMS
Relational DBMSSearch engineRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsSpatial DBMSTime Series DBMS infousing the Manticore Columnar LibraryDocument 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
Score0.49
Rank#259  Overall
#40  Document stores
#120  Relational DBMS
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score0.23
Rank#317  Overall
#21  Search engines
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score0.25
Rank#308  Overall
#26  Time Series DBMS
Websitealasql.orggithub.com/­heavyai/­heavydb
www.heavy.ai
manticoresearch.comazure.microsoft.com/­services/­data-explorer
Technical documentationgithub.com/­AlaSQL/­alasqldocs.heavy.aimanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperAndrey Gershun & Mathias R. WulffHEAVY.AI, Inc.Manticore SoftwareMicrosoftOpen Source, formerly Basho Technologies
Initial release20142016201720192015
Current release5.10, January 20226.0, February 2023cloud service with continuous releases3.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoMIT-LicenseOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGPL version 2commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptC++ and CUDAC++Erlang
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)LinuxFreeBSD
Linux
macOS
Windows
hostedLinux
OS X
Data schemeschema-freeyesFixed schemaFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or datenoyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.nonoCan index from XMLyesno
Secondary indexesnonoyes infofull-text index on all search fieldsall fields are automatically indexedrestricted
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.yesSQL-like query languageKusto Query Language (KQL), SQL subsetyes, limited
APIs and other access methodsJavaScript APIJDBC
ODBC
Thrift
Vega
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesJavaScriptAll languages supporting JDBC/ODBC/Thrift
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.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
Server-side scripts infoStored proceduresnonouser defined functionsYes, possible languages: KQL, Python, RErlang
Triggersyesnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoRound robinSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnononono infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storagenoyes infoisolated transactions for atomic changes and binary logging for safe writesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardnoAzure Active Directory Authenticationno

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More resources
AlaSQLHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Manticore SearchMicrosoft Azure Data ExplorerRiak TS
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