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DBMS > Microsoft Azure Data Explorer vs. Neo4j vs. SpaceTime vs. Sphinx vs. Splice Machine

System Properties Comparison Microsoft Azure Data Explorer vs. Neo4j vs. SpaceTime vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonNeo4j  Xexclude from comparisonSpaceTime  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsSpaceTime is a spatio-temporal DBMS with a focus on performance.Open source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS infocolumn orientedGraph DBMSSpatial DBMSSearch engineRelational 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerneo4j.comwww.mireo.com/­spacetimesphinxsearch.comsplicemachine.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerneo4j.com/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperMicrosoftNeo4j, Inc.MireoSphinx Technologies Inc.Splice Machine
Initial release20192007202020012014
Current releasecloud service with continuous releases5.20, May 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoGPL version3, commercial licenses availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJava, ScalaC++C++Java
Server operating systemshostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)schema-free and schema-optionalyesyesyes
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesnoyes
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.yesno
Secondary indexesall fields are automatically indexedyes infopluggable indexing subsystem, by default Apache Lucenenoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnoA subset of ANSI SQL is implementedSQL-like query language (SphinxQL)yes
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
RESTful HTTP APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
C#
C++
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Ryes infoUser defined Procedures and Functionsnonoyes infoJava
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handlernonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceyes using Neo4j FabricFixed-grid hypercubesSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Causal Clustering using Raft protocol infoavailable in in Enterprise Version onlyReal-time block device replication (DRBD)noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAzure Active Directory AuthenticationUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)yesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Microsoft Azure Data ExplorerNeo4jSpaceTimeSphinxSplice Machine
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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