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DBMS > EventStoreDB vs. Faircom EDGE vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. Tkrzw

System Properties Comparison EventStoreDB vs. Faircom EDGE vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. Tkrzw

Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsEmbeddable relational database for web apps written in pure JavaScriptElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelEvent StoreKey-value store
Relational DBMS
Relational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.10
Rank#179  Overall
#1  Event Stores
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.eventstore.comwww.faircom.com/­products/­faircom-edgegoogle.github.io/­lovefieldazure.microsoft.com/­services/­synapse-analyticsdbmx.net/­tkrzw
Technical documentationdevelopers.eventstore.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­azure/­synapse-analytics
DeveloperEvent Store LimitedFairCom CorporationGoogleMicrosoftMikio Hirabayashi
Initial release20121979201420162020
Current release21.2, February 2021V3, October 20202.1.12, February 20170.9.3, August 2020
License infoCommercial or Open SourceOpen Sourcecommercial infoRestricted, free version availableOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++JavaScriptC++C++
Server operating systemsLinux
Windows
Android
Linux infoARM, x86
Raspbian
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyesyesno
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.yesnonono
Secondary indexesyesyesyes
SQL infoSupport of SQLyes infoANSI SQL queriesSQL-like query language infovia JavaScript builder patternyesno
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
JavaScriptC#
Java
PHP
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noTransact SQLno
TriggersyesUsing read-only observersnono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningnoneSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDByes infousing specific database classes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.noyesno

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More resources
EventStoreDBFaircom EDGE infoformerly c-treeEDGELovefieldMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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