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

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

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonHugeGraph  Xexclude from comparisonSequoiadb  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA fast-speed and highly-scalable Graph DBMSNewSQL database with distributed OLTP and SQLIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMS
RDF store
Graph DBMSDocument store
Relational DBMS
Document 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
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational 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.sequoiadb.comwww.tarantool.io
Technical documentationaws.amazon.com/­neptune/­developer-resourceshugegraph.apache.org/­docswww.sequoiadb.com/­en/­index.php?m=Files&a=indexwww.tarantool.io/­en/­doc
DeveloperAmazonBaiduSequoiadb Ltd.VK
Initial release2017201820132008
Current release0.92.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoServer: AGPL; Client: Apache V2Open 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++C and C++
Server operating systemshostedLinux
macOS
Unix
LinuxBSD
Linux
macOS
Data schemeschema-freeyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyes infooid, date, timestamp, binary, regexstring, 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.nononono
Secondary indexesnoyes infoalso supports composite index and range indexyesyes
SQL infoSupport of SQLnonoSQL-like query languageFull-featured ANSI SQL support
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP API
TinkerPop Gremlin
proprietary protocol using JSONOpen binary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Groovy
Java
Python
.Net
C++
Java
PHP
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsJavaScriptLua, C and SQL stored procedures
Triggersnononoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesnoneyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding, 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.yes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationAsynchronous 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 methodsnovia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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 integrityyes infoRelationships in graphsyes infoedges in graphnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDDocument is locked during a transactionACID, 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.yesnoyes, 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)Users, roles and permissionssimple password-based access controlAccess 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 NeptuneHugeGraphSequoiadbTarantool
DB-Engines blog posts

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

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