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DBMS > Apache Impala vs. EDB Postgres vs. Faircom DB vs. HugeGraph

System Properties Comparison Apache Impala vs. EDB Postgres vs. Faircom DB vs. HugeGraph

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEDB Postgres  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Native 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 modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Graph DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.91
Rank#130  Overall
#60  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websiteimpala.apache.orgwww.enterprisedb.comwww.faircom.com/­products/­faircom-dbgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlwww.enterprisedb.com/­docsdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlhugegraph.apache.org/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEnterpriseDBFairCom CorporationBaidu
Initial release2013200519792018
Current release4.1.0, June 202214, December 2021V12, November 20200.9
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoBSD for PostgreSQL-componentscommercial infoRestricted, free version availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CANSI C, C++Java
Server operating systemsLinuxLinux
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
macOS
Unix
Data schemeyesyesschema 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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard with numerous extensionsyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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 languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Groovy
Java
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes info.Net, JavaScript, C/C++asynchronous Gremlin script jobs
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoby hash, list or rangeFile 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 nodesselectable replication factorMulti-source replicationyes, 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 methodsyes infoquery execution via MapReducenonovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Foreign keys infoReferential integritynoyesyesyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDtunable from ACID to Eventually ConsistentACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesYes, 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.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardFine grained access rights according to SQL-standard with additional protections for filesUsers, roles and permissions

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More resources
Apache ImpalaEDB PostgresFaircom DB infoformerly c-treeACEHugeGraph
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