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DBMS > Amazon Neptune vs. Faircom DB vs. GeoMesa vs. Spark SQL vs. Transbase

System Properties Comparison Amazon Neptune vs. Faircom DB vs. GeoMesa vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGeoMesa  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Spark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelGraph DBMS
RDF store
Key-value store
Relational DBMS
Spatial DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websiteaws.amazon.com/­neptunewww.faircom.com/­products/­faircom-dbwww.geomesa.orgspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.geomesa.org/­documentation/­stable/­user/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperAmazonFairCom CorporationCCRi and othersApache Software FoundationTransaction Software GmbH
Initial release20171979201420141987
Current releaseV12, November 20205.0.0, May 20243.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoApache License 2.0Open Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++ScalaScalaC and C++
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeschema free, schema optional, schema required, partial schema,yesyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes
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.nonononono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsnoSQL-like DML and DDL statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++nonoyes
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningdepending on storage layeryes, utilizing Spark Core
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, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).depending on storage layernoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
depending on storage layerImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually Consistentnonoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesdepending on storage layernono
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-standard with additional protections for filesyes infodepending on the DBMS used for storagenofine grained access rights according to SQL-standard

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More resources
Amazon NeptuneFaircom DB infoformerly c-treeACEGeoMesaSpark SQLTransbase
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