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DBMS > Microsoft Azure Table Storage vs. Rockset vs. Tarantool vs. VoltDB

System Properties Comparison Microsoft Azure Table Storage vs. Rockset vs. Tarantool vs. VoltDB

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonRockset  Xexclude from comparisonTarantool  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsA scalable, reliable search and analytics service in the cloud, built on RocksDBIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelWide column storeDocument storeDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsRelational DBMS
Search engine
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.79
Rank#211  Overall
#35  Document stores
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score1.44
Rank#158  Overall
#73  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesrockset.comwww.tarantool.iowww.voltdb.com
Technical documentationdocs.rockset.comwww.tarantool.io/­en/­docdocs.voltdb.com
DeveloperMicrosoftRocksetVKVoltDB Inc.
Initial release2012201920082010
Current release2.10.0, May 202211.3, April 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++Java, C++
Server operating systemshostedhostedBSD
Linux
macOS
Linux
OS X infofor development
Data schemeschema-freeschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesdynamic typingstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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.nono infoingestion from XML files supportedno
Secondary indexesnoall fields are automatically indexedyesyes
SQL infoSupport of SQLnoRead-only SQL queries, including JOINsFull-featured ANSI SQL supportyes infoonly a subset of SQL 99
APIs and other access methodsRESTful HTTP APIHTTP RESTOpen binary protocolJava API
JDBC
RESTful HTTP/JSON API
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresnonoLua, C and SQL stored proceduresJava
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 serviceAutomatic shardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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 integritynonoyesno infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesAccess rights for users and organizations can be defined via Rockset consoleAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Users and roles with access to stored procedures

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More resources
Microsoft Azure Table StorageRocksetTarantoolVoltDB
DB-Engines blog posts

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

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