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DBMS > GigaSpaces vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer

System Properties Comparison GigaSpaces vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonHeroic  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platform
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsGraph DBMS
Search engine
Document 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
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score0.35
Rank#283  Overall
#41  Key-value stores
#128  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitewww.gigaspaces.comgithub.com/­spotify/­heroicwww.leanxcale.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperGigaspaces TechnologiesSpotifyLeanXcaleMicrosoft
Initial release2000201420152019
Current release15.5, September 2020cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetJava
Server operating systemsLinux
macOS
Solaris
Windows
hosted
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.no infoXML can be used for describing objects metadatanoyes
Secondary indexesyesyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLSQL-99 for query and DML statementsnoyes infothrough Apache DerbyKusto Query Language (KQL), SQL subset
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C++
Java
Python
Scala
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, R
Triggersyes, event driven architecturenoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlRole-based access controlAzure Active Directory Authentication

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More resources
GigaSpacesHeroicLeanXcaleMicrosoft Azure Data Explorer
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