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DBMS > Amazon Neptune vs. Kyligence Enterprise vs. LevelDB vs. Tarantool

System Properties Comparison Amazon Neptune vs. Kyligence Enterprise vs. LevelDB vs. Tarantool

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonLevelDB  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA distributed analytics engine for big data, built on top of Apache KylinEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value storeDocument 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
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.40
Rank#269  Overall
#124  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websiteaws.amazon.com/­neptunekyligence.io/­kyligence-enterprisegithub.com/­google/­leveldbwww.tarantool.io
Technical documentationaws.amazon.com/­neptune/­developer-resourcesgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.tarantool.io/­en/­doc
DeveloperAmazonKyligence, Inc.GoogleVK
Initial release2017201620112008
Current release1.23, February 20212.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDOpen 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 systemshostedLinuxIllumos
Linux
OS X
Windows
BSD
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 dateyesyesnostring, 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 indexesnoyesnoyes
SQL infoSupport of SQLnoANSI SQL for queries (using Apache Calcite)noFull-featured ANSI SQL support
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Open binary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnonoLua, C and SQL stored procedures
Triggersnonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding, 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.noneAsynchronous 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 methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, 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-restyesyes infowith automatic compression on writesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, 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)noAccess 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 NeptuneKyligence EnterpriseLevelDBTarantool
DB-Engines blog posts

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

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