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DBMS > HugeGraph vs. Ignite vs. Microsoft Azure Data Explorer vs. Spark SQL vs. Teradata

System Properties Comparison HugeGraph vs. Ignite vs. Microsoft Azure Data Explorer vs. Spark SQL vs. Teradata

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelGraph DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMSRelational DBMS
Secondary database modelsDocument 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
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
ignite.apache.orgazure.microsoft.com/­services/­data-explorerspark.apache.org/­sqlwww.teradata.com
Technical documentationhugegraph.apache.org/­docsapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperBaiduApache Software FoundationMicrosoftApache Software FoundationTeradata
Initial release20182015201920141984
Current release0.9Apache Ignite 2.6cloud service with continuous releases3.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Java, .NetScala
Server operating systemsLinux
macOS
Unix
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
hosted
Linux
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesyes
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-typesyesyes
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.noyesyesnoyes
Secondary indexesyes infoalso supports composite index and range indexyesall fields are automatically indexednoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesGroovy
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, Rnoyes infoUDFs, stored procedures, table functions in parallel
Triggersnoyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparkyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnonoyes
User concepts infoAccess controlUsers, roles and permissionsSecurity Hooks for custom implementationsAzure Active Directory Authenticationnofine grained access rights according to SQL-standard

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More resources
HugeGraphIgniteMicrosoft Azure Data ExplorerSpark SQLTeradata
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