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DBMS > GridGain vs. Microsoft Azure Data Explorer vs. Teradata Aster vs. TinkerGraph vs. Warp 10

System Properties Comparison GridGain vs. Microsoft Azure Data Explorer vs. Teradata Aster vs. TinkerGraph vs. Warp 10

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTinkerGraph  Xexclude from comparisonWarp 10  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteFully managed big data interactive analytics platformPlatform for big data analytics on multistructured data sources and typesA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 APITimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMSGraph DBMSTime Series 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score0.08
Rank#345  Overall
#34  Graph DBMS
Score0.06
Rank#351  Overall
#35  Time Series DBMS
Websitewww.gridgain.comazure.microsoft.com/­services/­data-explorertinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlinwww.warp10.io
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.warp10.io/­content/­02_Getting_started
DeveloperGridGain Systems, Inc.MicrosoftTeradataSenX
Initial release20072019200520092015
Current releaseGridGain 8.5.1cloud service with continuous releases
License infoCommercial or Open Sourcecommercial, open sourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache License 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.
Implementation languageJava, C++, .Net, Python, REST, SQLJavaJava
Server operating systemsLinux
OS X
Solaris
Windows
z/OS
hostedLinuxLinux
OS X
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)Flexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-freeschema-free
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-typesyesyesyes
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.yesyesyes infoin Aster File Storenono
Secondary indexesyesall fields are automatically indexedyesnono
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetyesnono
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
TinkerPop 3HTTP API
Jupyter
WebSocket
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Java
Python
R
Groovy
Java
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, RR packagesnoyes infoWarpScript
Triggersyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingnoneSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.noneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparkyes infoSQL Map-Reduce Frameworknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationnoneImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
Durability infoSupport for making data persistentyesyesyesoptionalyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesyes
User concepts infoAccess controlRole-based access control
Security Hooks for custom implementations
Azure Active Directory Authenticationfine grained access rights according to SQL-standardnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
GridGainMicrosoft Azure Data ExplorerTeradata AsterTinkerGraphWarp 10
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