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DBMS > Amazon DocumentDB vs. DolphinDB vs. Tarantool vs. TinkerGraph

System Properties Comparison Amazon DocumentDB vs. DolphinDB vs. Tarantool vs. TinkerGraph

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDolphinDB  Xexclude from comparisonTarantool  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.In-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument storeTime Series DBMSDocument store
Key-value store
Relational DBMS
Graph DBMS
Secondary database modelsRelational DBMSSpatial 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
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websiteaws.amazon.com/­documentdbwww.dolphindb.comwww.tarantool.iotinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.dolphindb.cn/­en/­help200/­index.htmlwww.tarantool.io/­en/­doc
DeveloperDolphinDB, IncVK
Initial release2019201820082009
Current releasev2.00.4, January 20222.10.0, May 2022
License infoCommercial or Open Sourcecommercialcommercial infofree community version availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++Java
Server operating systemshostedLinux
Windows
BSD
Linux
macOS
Data schemeschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsschema-free
Typing infopredefined data types such as float or dateyesyesstring, 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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoSQL-like query languageFull-featured ANSI SQL supportno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Open binary protocolTinkerPop 3
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Groovy
Java
Server-side scripts infoStored proceduresnoyesLua, 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 nodesnonehorizontal partitioningSharding, 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 nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesAsynchronous 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 methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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
none
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyesACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingno
Durability infoSupport for making data persistentyesyesyes, write ahead loggingoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, full featured in-memory storage engine with persistenceyes
User concepts infoAccess controlAccess rights for users and rolesAdministrators, Users, GroupsAccess 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
Amazon DocumentDBDolphinDBTarantoolTinkerGraph
DB-Engines blog posts

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

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