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DBMS > HEAVY.AI vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. SpatiaLite vs. Tarantool

System Properties Comparison HEAVY.AI vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. SpatiaLite vs. Tarantool

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 comparisonOracle Berkeley DB  Xexclude from comparisonSpatiaLite  Xexclude from comparisonTarantool  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 platformWidely used in-process key-value storeSpatial extension of SQLiteIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSRelational DBMS infocolumn orientedKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Spatial DBMSDocument store
Key-value store
Relational 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 DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Score1.72
Rank#149  Overall
#3  Spatial DBMS
Score1.67
Rank#150  Overall
#25  Document stores
#25  Key-value stores
#69  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.gaia-gis.it/­fossil/­libspatialite/­indexwww.tarantool.io
Technical documentationdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.gaia-gis.it/­gaia-sins/­spatialite_topics.htmlwww.tarantool.io/­en/­doc
DeveloperHEAVY.AI, Inc.MicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleAlessandro FurieriVK
Initial release20162019199420082008
Current release5.10, January 2022cloud service with continuous releases18.1.40, May 20205.0.0, August 20202.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infocommercial license availableOpen Source infoMPL 1.1, GPL v2.0 or LGPL v2.1Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
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++ and CUDAC, Java, C++ (depending on the Berkeley DB edition)C++C and C++
Server operating systemsLinuxhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
server-lessBSD
Linux
macOS
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
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-typesnoyesstring, 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.noyesyes infoonly with the Berkeley DB XML editionnono
Secondary indexesnoall fields are automatically indexedyesyesyes
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetyes infoSQL interfaced based on SQLite is availableyesFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Open binary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RnonoLua, C and SQL stored procedures
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL APIyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infoImplicit feature of the cloud servicenonenoneSharding, 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 nodesMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnoneAsynchronous 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 methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Casual 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 datanonoACIDACIDACID, 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 persistentyesyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationnonoAccess 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
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerOracle Berkeley DBSpatiaLiteTarantool
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