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DBMS > Citus vs. EXASOL vs. Microsoft Azure Data Explorer vs. SwayDB vs. Tarantool

System Properties Comparison Citus vs. EXASOL vs. Microsoft Azure Data Explorer vs. SwayDB vs. Tarantool

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonEXASOL  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSwayDB  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Fully managed big data interactive analytics platformAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storageIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedKey-value storeDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument storeDocument 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
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score0.04
Rank#373  Overall
#57  Key-value stores
Score1.67
Rank#150  Overall
#25  Document stores
#25  Key-value stores
#69  Relational DBMS
Websitewww.citusdata.comwww.exasol.comazure.microsoft.com/­services/­data-explorerswaydb.simer.auwww.tarantool.io
Technical documentationdocs.citusdata.comwww.exasol.com/­resourcesdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tarantool.io/­en/­doc
DeveloperExasolMicrosoftSimer PlahaVK
Initial release20102000201920182008
Current release8.1, December 2018cloud service with continuous releases2.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialOpen Source infoGNU Affero GPL V3.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCScalaC and C++
Server operating systemsLinuxhostedBSD
Linux
macOS
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnostring, 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.yes infospecific XML type available, but no XML query functionalitynoyesnono
Secondary indexesyesyesall fields are automatically indexednoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyesKusto Query Language (KQL), SQL subsetnoFull-featured ANSI SQL support
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
.Net
JDBC
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Open binary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Kotlin
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functionsYes, possible languages: KQL, Python, RnoLua, C and SQL stored procedures
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenoneSharding, 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 nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneAsynchronous 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 methodsnoyes infoHadoop integrationSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoAtomic execution of operationsACID, 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 persistentyesyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAzure Active Directory AuthenticationnoAccess 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
CitusEXASOLMicrosoft Azure Data ExplorerSwayDBTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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