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DBMS > Machbase Neo vs. Microsoft Azure Data Explorer vs. Spark SQL vs. Sphinx vs. Tarantool

System Properties Comparison Machbase Neo vs. Microsoft Azure Data Explorer vs. Spark SQL vs. Sphinx vs. Tarantool

Editorial information provided by DB-Engines
NameMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionTimeSeries DBMS for AIoT and BigDataFully managed big data interactive analytics platformSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedRelational DBMSSearch engineDocument store
Key-value store
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
Score0.17
Rank#337  Overall
#30  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitemachbase.comazure.microsoft.com/­services/­data-explorerspark.apache.org/­sqlsphinxsearch.comwww.tarantool.io
Technical documentationmachbase.com/­dbmsdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docswww.tarantool.io/­en/­doc
DeveloperMachbaseMicrosoftApache Software FoundationSphinx Technologies Inc.VK
Initial release20132019201420012008
Current releaseV8.0, August 2023cloud service with continuous releases3.5.0 ( 2.13), September 20233.5.1, February 20232.10.0, May 2022
License infoCommercial or Open Sourcecommercial infofree test version availablecommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
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 languageCScalaC++C and C++
Server operating systemsLinux
macOS
Windows
hostedLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
BSD
Linux
macOS
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
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-typesyesnostring, double, decimal, uuid, integer, blob, boolean, datetime
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.noyesnono
Secondary indexesyesall fields are automatically indexednoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsSQL-like query language (SphinxQL)Full-featured ANSI SQL support
APIs and other access methodsgRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocolOpen binary protocol
Supported programming languagesC
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RnonoLua, C and SQL stored procedures
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding, 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 nodesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonenoneAsynchronous 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-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Casual 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 integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentnoyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infovolatile and lookup tablenonoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlsimple password-based access controlAzure Active Directory AuthenticationnonoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
Machbase Neo infoFormer name was InfinifluxMicrosoft Azure Data ExplorerSpark SQLSphinxTarantool
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