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DBMS > Cloudflare Workers KV vs. Microsoft Azure Table Storage vs. Tarantool vs. Tkrzw

System Properties Comparison Cloudflare Workers KV vs. Microsoft Azure Table Storage vs. Tarantool vs. Tkrzw

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Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTarantool  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.A Wide Column Store for rapid development using massive semi-structured datasetsIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA 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 modelKey-value storeWide column storeDocument store
Key-value store
Relational DBMS
Key-value store
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#283  Overall
#40  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.cloudflare.com/­developer-platform/­workers-kvazure.microsoft.com/­en-us/­services/­storage/­tableswww.tarantool.iodbmx.net/­tkrzw
Technical documentationdevelopers.cloudflare.com/­kv/­apiwww.tarantool.io/­en/­doc
DeveloperCloudflareMicrosoftVKMikio Hirabayashi
Initial release2018201220082020
Current release2.10.0, May 20220.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++
Server operating systemshostedhostedBSD
Linux
macOS
Linux
macOS
Data schemeschema-freeschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columnsschema-free
Typing infopredefined data types such as float or datenoyesstring, double, decimal, uuid, integer, blob, boolean, datetimeno
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.nononono
Secondary indexesnonoyes
SQL infoSupport of SQLnonoFull-featured ANSI SQL supportno
APIs and other access methodsHTTP REST
Proprietary protocol
RESTful HTTP APIOpen binary protocol
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnonoLua, C and SQL stored proceduresno
Triggersnonoyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.none
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, 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 infousing specific database classes
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
no

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More resources
Cloudflare Workers KVMicrosoft Azure Table StorageTarantoolTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
DB-Engines blog posts

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

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