DBMS > Galaxybase vs. Lovefield vs. Microsoft Azure AI Search vs. Microsoft Azure Data Explorer

System Properties Comparison Galaxybase vs. Lovefield vs. Microsoft Azure AI Search vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
Name	Galaxybase  Xexclude from comparison	Lovefield  Xexclude from comparison	Microsoft Azure AI Search  Xexclude from comparison	Microsoft Azure Data Explorer  Xexclude from comparison
Description	Scalable, ACID-compliant native distributed parallel graph platform	Embeddable relational database for web apps written in pure JavaScript	Search-as-a-service for web and mobile app development	Fully managed big data interactive analytics platform
Primary database model	Graph DBMS	Relational DBMS	Search engine	Relational DBMS column oriented
Secondary database models			Vector DBMS	Document store If 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 this 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 support 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 see docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 0.07 Rank #377   Overall #40   Graph DBMS	Score 0.33 Rank #286   Overall #131   Relational DBMS	Score 5.52 Rank #59   Overall #6   Search engines	Score 3.80 Rank #81   Overall #43   Relational DBMS
Website	galaxybase.com	google.github.io/­lovefield	azure.microsoft.com/­en-us/­services/­search	azure.microsoft.com/­services/­data-explorer
Technical documentation		github.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md	learn.microsoft.com/­en-us/­azure/­search	docs.microsoft.com/­en-us/­azure/­data-explorer
Developer	Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司	Google	Microsoft	Microsoft
Initial release	2017	2014	2015	2019
Current release	Nov 20, November 2021	2.1.12, February 2017	V1	cloud service with continuous releases
License Commercial or Open Source	commercial	Open Source Apache 2.0	commercial	commercial
Cloud-based only Only available as a cloud service	no	no	yes	yes
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	C and Java	JavaScript
Server operating systems	Linux	server-less, requires a JavaScript environment (browser, Node.js) tested with Chrome, Firefox, IE, Safari	hosted	hosted
Data scheme	Strong typed schema	yes	yes	Fixed schema with schema-less datatypes (dynamic)
Typing predefined data types such as float or date	yes	yes	yes	yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.	no	no	no	yes
Secondary indexes	yes	yes	yes	all fields are automatically indexed
SQL Support of SQL	no	SQL-like query language via JavaScript builder pattern	no	Kusto Query Language (KQL), SQL subset
APIs and other access methods	Browser interface console (shell) Graph API (Gremlin) OpenCypher Proprietary native API		RESTful HTTP API	Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API
Supported programming languages	Go Java Python	JavaScript	C# Java JavaScript Python	.Net Go Java JavaScript (Node.js) PowerShell Python R
Server-side scripts Stored procedures	user defined procedures and functions	no	no	Yes, possible languages: KQL, Python, R
Triggers		Using read-only observers	no	yes see docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods Methods for storing different data on different nodes	Sharding	none	Sharding Implicit feature of the cloud service	Sharding Implicit feature of the cloud service
Replication methods Methods for redundantly storing data on multiple nodes		none	yes Implicit feature of the cloud service	yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce Offers an API for user-defined Map/Reduce methods	no	no	no	Spark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency		Immediate Consistency	Eventual Consistency Immediate Consistency
Foreign keys Referential integrity	yes Relationships in graphs	yes	no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	ACID	ACID	no	no
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes, by using IndexedDB or the cloud service Firebase Realtime Database	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	yes using MemoryDB	no	no
User concepts Access control	Role-based access control	no	yes using Azure authentication	Azure Active Directory Authentication
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More resources
	Galaxybase	Lovefield	Microsoft Azure AI Search	Microsoft Azure Data Explorer
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