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DBMS > Amazon Neptune vs. Tarantool vs. TigerGraph vs. ToroDB

System Properties Comparison Amazon Neptune vs. Tarantool vs. TigerGraph vs. ToroDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonTarantool  Xexclude from comparisonTigerGraph  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFast, reliable graph database built for the cloudIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelGraph DBMS
RDF store
Document store
Key-value store
Relational DBMS
Graph DBMSDocument store
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteaws.amazon.com/­neptunewww.tarantool.iowww.tigergraph.comgithub.com/­torodb/­server
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.tarantool.io/­en/­docdocs.tigergraph.com
DeveloperAmazonVK8Kdata
Initial release2017200820172016
Current release2.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterprisecommercialOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++Java
Server operating systemshostedBSD
Linux
macOS
LinuxAll OS with a Java 7 VM
Data schemeschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyesschema-free
Typing infopredefined data types such as float or dateyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyesyes infostring, integer, double, boolean, date, object_id
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 indexesnoyes
SQL infoSupport of SQLnoFull-featured ANSI SQL supportSQL-like query language (GSQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Open binary protocolGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C++
Java
Server-side scripts infoStored proceduresnoLua, C and SQL stored proceduresyes
Triggersnoyes, before/after data modification events, on replication events, client session eventsnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding, 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 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.Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, cooperative multitaskingyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes, write ahead loggingyesyes
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 persistenceno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Role-based access controlAccess rights for users and roles

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More resources
Amazon NeptuneTarantoolTigerGraphToroDB
DB-Engines blog posts

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

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