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DBMS > Amazon Neptune vs. etcd vs. InfinityDB vs. Sadas Engine vs. Spark SQL

System Properties Comparison Amazon Neptune vs. etcd vs. InfinityDB vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonetcd  Xexclude from comparisonInfinityDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA distributed reliable key-value storeA Java embedded Key-Value Store which extends the Java Map interfaceSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Key-value storeKey-value storeRelational DBMSRelational 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
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.00
Rank#378  Overall
#57  Key-value stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptuneetcd.io
github.com/­etcd-io/­etcd
boilerbay.comwww.sadasengine.comspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
boilerbay.com/­infinitydb/­manualwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonBoiler Bay Inc.SADAS s.r.l.Apache Software Foundation
Initial release2017200220062014
Current release3.4, August 20194.08.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial infofree trial version availableOpen 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 languageGoJavaC++Scala
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
All OS with a Java VMAIX
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or dateyesnoyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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 indexesnonono infomanual creation possible, using inversions based on multi-value capabilityyesno
SQL infoSupport of SQLnononoyesSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC
JSON over HTTP
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonononono
Triggersnoyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioningyes, 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.Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.nonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnono infomanual creation possible, using inversions based on multi-value capabilityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoOptimistic locking for transactions; no isolation for bulk loadsno
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 infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)nonoAccess rights for users, groups and roles according to SQL-standardno

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More resources
Amazon NeptuneetcdInfinityDBSadas EngineSpark SQL
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