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DBMS > HEAVY.AI vs. Microsoft Azure Data Explorer vs. Riak KV vs. SpatiaLite vs. YugabyteDB

System Properties Comparison HEAVY.AI vs. Microsoft Azure Data Explorer vs. Riak KV vs. SpatiaLite vs. YugabyteDB

Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonSpatiaLite  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platformDistributed, fault tolerant key-value storeSpatial extension of SQLiteHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSRelational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesSpatial DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument 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 DBMSDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score1.60
Rank#149  Overall
#3  Spatial DBMS
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorerwww.gaia-gis.it/­fossil/­libspatialite/­indexwww.yugabyte.com
Technical documentationdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latestwww.gaia-gis.it/­gaia-sins/­spatialite_topics.htmldocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperHEAVY.AI, Inc.MicrosoftOpenSource, formerly Basho TechnologiesAlessandro FurieriYugabyte Inc.
Initial release20162019200920082017
Current release5.10, January 2022cloud service with continuous releases3.2.0, December 20225.0.0, August 20202.19, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoMPL 1.1, GPL v2.0 or LGPL v2.1Open 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.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageC++ and CUDAErlangC++C and C++
Server operating systemsLinuxhostedLinux
OS X
server-lessLinux
OS X
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeyesdepending on used data model
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.noyesnonono
Secondary indexesnoall fields are automatically indexedrestrictedyesyes
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetnoyesyes, PostgreSQL compatible
APIs and other access methodsJDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
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
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RErlangnoyes infosql, plpgsql, C
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"noneHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factornoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynonono infolinks between data sets can be storedyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationyes, using Riak Securitynoyes
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerRiak KVSpatiaLiteYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerRiak KVSpatiaLiteYugabyteDB
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