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DBMS > Amazon Neptune vs. Microsoft Azure Data Explorer vs. OpenEdge vs. Tarantool vs. Valentina Server

System Properties Comparison Amazon Neptune vs. Microsoft Azure Data Explorer vs. OpenEdge vs. Tarantool vs. Valentina Server

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOpenEdge  Xexclude from comparisonTarantool  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudFully managed big data interactive analytics platformApplication development environment with integrated database management systemIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsObject-relational database and reports server
Primary database modelGraph DBMS
RDF store
Relational DBMS infocolumn orientedRelational DBMSDocument store
Key-value store
Relational DBMS
Relational 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
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score3.45
Rank#85  Overall
#46  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websiteaws.amazon.com/­neptuneazure.microsoft.com/­services/­data-explorerwww.progress.com/­openedgewww.tarantool.iowww.valentina-db.net
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.microsoft.com/­en-us/­azure/­data-explorerdocumentation.progress.com/­output/­ua/­OpenEdge_latestwww.tarantool.io/­en/­docvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperAmazonMicrosoftProgress Software CorporationVKParadigma Software
Initial release20172019198420081999
Current releasecloud service with continuous releasesOpenEdge 12.2, March 20202.10.0, May 20225.7.5
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++
Server operating systemshostedhostedAIX
HP-UX
Linux
Solaris
Windows
BSD
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
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-typesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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.noyesyesno
Secondary indexesnoall fields are automatically indexedyesyesyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetyes infoclose to SQL 92Full-featured ANSI SQL supportyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Open binary protocolODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Progress proprietary ABL (Advanced Business Language)C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RyesLua, C and SQL stored proceduresyes
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning infosince Version 11.4Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
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.yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes, full featured in-memory storage engine with persistenceyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Azure Active Directory AuthenticationUsers and groupsAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard

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More resources
Amazon NeptuneMicrosoft Azure Data ExplorerOpenEdgeTarantoolValentina Server
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
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