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DBMS > Amazon Neptune vs. CockroachDB vs. Elasticsearch vs. MarkLogic vs. Microsoft Azure Data Explorer

System Properties Comparison Amazon Neptune vs. CockroachDB vs. Elasticsearch vs. MarkLogic vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCockroachDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.A distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricOperational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platform
Primary database modelGraph DBMS
RDF store
Relational DBMSSearch engineDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn oriented
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
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
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteaws.amazon.com/­neptunewww.cockroachlabs.comwww.elastic.co/­elasticsearchwww.marklogic.comazure.microsoft.com/­services/­data-explorer
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.cockroachlabs.com/­docswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.marklogic.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAmazonCockroach LabsElasticMarkLogic Corp.Microsoft
Initial release20172015201020012019
Current release24.1.0, May 20248.6, January 202311.0, December 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0, commercial license availableOpen Source infoElastic Licensecommercial inforestricted free version is availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaC++
Server operating systemshostedLinux
macOS
Windows
All OS with a Java VMLinux
OS X
Windows
hosted
Data schemeschema-freedynamic schemaschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyesyes 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.nononoyesyes
Secondary indexesnoyesyes infoAll search fields are automatically indexedyesall fields are automatically indexed
SQL infoSupport of SQLnoyes, wire compatible with PostgreSQLSQL-like query languageyes infoSQL92Kusto Query Language (KQL), SQL subset
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCJava API
RESTful HTTP/JSON API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnonoyesyes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, R
Triggersnonoyes infoby using the 'percolation' featureyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Multi-source replication using RAFTyesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoES-Hadoop Connectoryes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationyes, with Range Indexesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Role-based access controlRole-based access control at the document and subdocument levelsAzure Active Directory Authentication

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More resources
Amazon NeptuneCockroachDBElasticsearchMarkLogicMicrosoft Azure Data Explorer
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