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DBMS > Amazon Neptune vs. Heroic vs. IBM Db2 warehouse vs. Tarantool

System Properties Comparison Amazon Neptune vs. Heroic vs. IBM Db2 warehouse vs. Tarantool

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonHeroic  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchCloud-based data warehousing serviceIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational 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
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score1.37
Rank#160  Overall
#74  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteaws.amazon.com/­neptunegithub.com/­spotify/­heroicwww.ibm.com/­products/­db2/­warehousewww.tarantool.io
Technical documentationaws.amazon.com/­neptune/­developer-resourcesspotify.github.io/­heroicwww.tarantool.io/­en/­doc
DeveloperAmazonSpotifyIBMVK
Initial release2017201420142008
Current release2.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++
Server operating systemshostedhostedBSD
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 infoImport/export of XML data possibleno
Secondary indexesnoyes infovia Elasticsearchyesyes
SQL infoSupport of SQLnonoyesFull-featured ANSI SQL support
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
HQL (Heroic Query Language, a JSON-based language)
HTTP API
.NET Client API
JDBC
ODBC
OLE DB
Open binary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnonoPL/SQL, SQL PLLua, C and SQL stored procedures
Triggersnonoyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding, 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.yesyesAsynchronous 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 methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate 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 graphsnoyesyes
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.noyesyes, 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)fine grained access rights according to SQL-standardAccess 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 NeptuneHeroicIBM Db2 warehouse infoformerly named IBM dashDBTarantool
DB-Engines blog posts

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

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