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DBMS > Amazon Neptune vs. Apache Druid vs. Dgraph vs. EsgynDB vs. Ignite

System Properties Comparison Amazon Neptune vs. Apache Druid vs. Dgraph vs. EsgynDB vs. Ignite

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Druid  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonIgnite  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Graph DBMSRelational DBMSKey-value store
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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websiteaws.amazon.com/­neptunedruid.apache.orgdgraph.iowww.esgyn.cnignite.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdruid.apache.org/­docs/­latest/­designdgraph.io/­docsapacheignite.readme.io/­docs
DeveloperAmazonApache Software Foundation and contributorsDgraph Labs, Inc.EsgynApache Software Foundation
Initial release20172012201620152015
Current release29.0.1, April 2024Apache Ignite 2.6
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoC++, JavaC++, Java, .Net
Server operating systemshostedLinux
OS X
Unix
Linux
OS X
Windows
LinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeyes infoschema-less columns are supportedschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonononoyes
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoSQL for queryingnoyesANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
RESTful HTTP/JSON API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnononoJava Stored Proceduresyes (compute grid and cache interceptors can be used instead)
Triggersnonononoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedyesShardingSharding
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, via HDFS, S3 or other storage enginesSynchronous replication via RaftMulti-source replication between multi datacentersyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyesyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)RBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemno infoPlanned for future releasesfine grained access rights according to SQL-standardSecurity Hooks for custom implementations

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More resources
Amazon NeptuneApache DruidDgraphEsgynDBIgnite
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