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DBMS > Amazon Neptune vs. Apache Impala vs. Faircom DB vs. HugeGraph

System Properties Comparison Amazon Neptune vs. Apache Impala vs. Faircom DB vs. HugeGraph

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Impala  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAnalytic DBMS for HadoopNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A fast-speed and highly-scalable Graph DBMS
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value store
Relational DBMS
Graph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#112  Overall
#9  Graph DBMS
#5  RDF stores
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score0.24
Rank#311  Overall
#44  Key-value stores
#140  Relational DBMS
Score0.15
Rank#339  Overall
#33  Graph DBMS
Websiteaws.amazon.com/­neptuneimpala.apache.orgwww.faircom.com/­products/­faircom-dbgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesimpala.apache.org/­impala-docs.htmldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlhugegraph.apache.org/­docs
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaFairCom CorporationBaidu
Initial release2017201319792018
Current release4.1.0, June 2022V12, November 20200.9
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infoRestricted, free version availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ANSI C, C++Java
Server operating systemshostedLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
macOS
Unix
Data schemeschema-freeyesschema free, schema optional, schema required, partial schema,yes
Typing infopredefined data types such as float or dateyesyesyes, ANSI SQL Types, JSON, typed binary structuresyes
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 indexesnoyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Groovy
Java
Python
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyes info.Net, JavaScript, C/C++asynchronous Gremlin script jobs
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningyes infodepending on used storage backend, e.g. Cassandra and HBase
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 factoryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnotunable from ACID to Eventually ConsistentACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
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 KerberosFine grained access rights according to SQL-standard with additional protections for filesUsers, roles and permissions

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More resources
Amazon NeptuneApache ImpalaFaircom DB infoformerly c-treeACEHugeGraph
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