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DBMS > Amazon DocumentDB vs. FileMaker vs. Hive vs. Tarantool

System Properties Comparison Amazon DocumentDB vs. FileMaker vs. Hive vs. Tarantool

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFileMaker  Xexclude from comparisonHive  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFileMaker is a cross-platform RDBMS that includes a GUI frontend.data warehouse software for querying and managing large distributed datasets, built on HadoopIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument storeRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.claris.com/­filemakerhive.apache.orgwww.tarantool.io
Technical documentationaws.amazon.com/­documentdb/­resourceswww.claris.com/­resources/­documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.tarantool.io/­en/­doc
DeveloperClaris infoa subsidiary of AppleApache Software Foundation infoinitially developed by FacebookVK
Initial release2019198320122008
Current release19.4.1, November 20213.1.3, April 20222.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++
Server operating systemshostediOS infoclient part only
Linux
OS X
Windows
All OS with a Java VMBSD
Linux
macOS
Data schemeschema-freeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, 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.noyes infoA http query request can return the data in XML formatno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyes infovia pluginsSQL-like DML and DDL statementsFull-featured ANSI SQL support
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Filemaker WebDirect
JDBC
ODBC
JDBC
ODBC
Thrift
Open binary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
PHPC++
Java
PHP
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyesyes infouser defined functions and integration of map-reduceLua, C and SQL stored procedures
Triggersnoyesnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding, 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 nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSource-replica replication, warm standby infosince Version 14selectable replication factorAsynchronous 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 methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes infoquery execution via MapReduce
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 integrityno infotypically not used, however similar functionality with DBRef possibleyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users and rolessimple rights management via user accounts and connection to external directory servicesAccess rights for users, groups and rolesAccess 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
Amazon DocumentDBFileMakerHiveTarantool
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