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DBMS > Amazon Neptune vs. FatDB vs. HugeGraph vs. Tarantool

System Properties Comparison Amazon Neptune vs. FatDB vs. HugeGraph vs. Tarantool

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFatDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonTarantool  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionFast, reliable graph database built for the cloudA .NET NoSQL DBMS that can integrate with and extend SQL Server.A fast-speed and highly-scalable Graph DBMSIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMS
RDF store
Document store
Key-value store
Graph 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
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteaws.amazon.com/­neptunegithub.com/­hugegraph
hugegraph.apache.org
www.tarantool.io
Technical documentationaws.amazon.com/­neptune/­developer-resourceshugegraph.apache.org/­docswww.tarantool.io/­en/­doc
DeveloperAmazonFatCloudBaiduVK
Initial release2017201220182008
Current release0.92.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open 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 languageC#JavaC and C++
Server operating systemshostedWindowsLinux
macOS
Unix
BSD
Linux
macOS
Data schemeschema-freeschema-freeyesFlexible 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.nonono
Secondary indexesnoyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServernoFull-featured ANSI SQL support
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Java API
RESTful HTTP API
TinkerPop Gremlin
Open binary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#Groovy
Java
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyes infovia applicationsasynchronous Gremlin script jobsLua, C and SQL stored procedures
Triggersnoyes infovia applicationsnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding, 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 high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.selectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseAsynchronous 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 methodsnoyesvia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual 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 integrityyes infoRelationships in graphsnoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID, 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 persistentyes infowith encyption-at-restyesyesyes, write ahead logging
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 persistence
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)no infoCan implement custom security layer via applicationsUsers, roles and permissionsAccess 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 NeptuneFatDBHugeGraphTarantool
DB-Engines blog posts

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

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