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DBMS > Amazon Neptune vs. Elasticsearch vs. Spark SQL vs. TDengine

System Properties Comparison Amazon Neptune vs. Elasticsearch vs. Spark SQL vs. TDengine

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonElasticsearch  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS and big data platform
Primary database modelGraph DBMS
RDF store
Search engineRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score135.35
Rank#7  Overall
#1  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteaws.amazon.com/­neptunewww.elastic.co/­elasticsearchspark.apache.org/­sqlgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tdengine.com
DeveloperAmazonElasticApache Software FoundationTDEngine, previously Taos Data
Initial release2017201020142019
Current release8.6, January 20233.5.0 ( 2.13), September 20233.0, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicenseOpen Source infoApache 2.0Open Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
Linux
Windows
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 infoAll search fields are automatically indexednono
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsStandard SQL with extensions for time-series applications
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyes infoby using the 'percolation' featurenoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark CoreSharding
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.yesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connector
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noyes
More information provided by the system vendor
Amazon NeptuneElasticsearchSpark SQLTDengine
Specific characteristicsTDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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