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DBMS > Databricks vs. Ehcache vs. Microsoft Azure Data Explorer vs. TigerGraph

System Properties Comparison Databricks vs. Ehcache vs. Microsoft Azure Data Explorer vs. TigerGraph

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A widely adopted Java cache with tiered storage optionsFully managed big data interactive analytics platformA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMS infocolumn orientedGraph 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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitewww.databricks.comwww.ehcache.orgazure.microsoft.com/­services/­data-explorerwww.tigergraph.com
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.tigergraph.com
DeveloperDatabricksTerracotta Inc, owned by Software AGMicrosoft
Initial release2013200920192017
Current release3.10.0, March 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedAll OS with a Java VMhostedLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeFixed schema with schema-less datatypes (dynamic)yes
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-typesyes
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.yesnoyesno
Secondary indexesyesnoall fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLnoKusto Query Language (KQL), SQL subsetSQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
Java.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoYes, possible languages: KQL, Python, Ryes
Triggersyes infoCache Event Listenersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta Serveryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourcenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlnoAzure Active Directory AuthenticationRole-based access control
More information provided by the system vendor
DatabricksEhcacheMicrosoft Azure Data ExplorerTigerGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEhcacheMicrosoft Azure Data ExplorerTigerGraph
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