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DBMS > Amazon Neptune vs. Apache Impala vs. OpenEdge vs. Splice Machine vs. WakandaDB

System Properties Comparison Amazon Neptune vs. Apache Impala vs. OpenEdge vs. Splice Machine vs. WakandaDB

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Impala  Xexclude from comparisonOpenEdge  Xexclude from comparisonSplice Machine  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAnalytic DBMS for HadoopApplication development environment with integrated database management systemOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.45
Rank#85  Overall
#46  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websiteaws.amazon.com/­neptuneimpala.apache.orgwww.progress.com/­openedgesplicemachine.comwakanda.github.io
Technical documentationaws.amazon.com/­neptune/­developer-resourcesimpala.apache.org/­impala-docs.htmldocumentation.progress.com/­output/­ua/­OpenEdge_latestsplicemachine.com/­how-it-workswakanda.github.io/­doc
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaProgress Software CorporationSplice MachineWakanda SAS
Initial release20172013198420142012
Current release4.1.0, June 2022OpenEdge 12.2, March 20203.1, March 20212.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++, JavaScript
Server operating systemshostedLinuxAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyesyes
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.nonoyesno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infoclose to SQL 92yesno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCProgress proprietary ABL (Advanced Business Language)C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesyes infoJavayes
Triggersnonoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infosince Version 11.4Shared Nothhing Auto-Sharding, Columnar Partitioningnone
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.selectable replication factorSource-replica replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
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.nonoyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles infobased on Apache Sentry and KerberosUsers and groupsAccess rights for users, groups and roles according to SQL-standardyes

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More resources
Amazon NeptuneApache ImpalaOpenEdgeSplice MachineWakandaDB
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