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DBMS > Apache Impala vs. Dragonfly vs. Faircom DB vs. HugeGraph

System Properties Comparison Apache Impala vs. Dragonfly vs. Faircom DB vs. HugeGraph

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDragonfly  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceNative 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 DBMSKey-value storeKey-value store
Relational DBMS
Graph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.49
Rank#261  Overall
#38  Key-value stores
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websiteimpala.apache.orggithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.faircom.com/­products/­faircom-dbgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlwww.dragonflydb.io/­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 ClouderaDragonflyDB team and community contributorsFairCom CorporationBaidu
Initial release2013202319792018
Current release4.1.0, June 20221.0, March 2023V12, November 20200.9
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSL 1.1commercial 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++C++ANSI C, C++Java
Server operating systemsLinuxLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
macOS
Unix
Data schemeyesscheme-freeschema free, schema optional, schema required, partial schema,yes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyes, 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 indexesyesnoyesyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoRESP - REdis Serialization ProtocolADO.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/ODBCC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
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-reduceLuayes info.Net, JavaScript, C/C++asynchronous Gremlin script jobs
Triggersnopublish/subscribe channels provide some trigger functionalityyesno
Partitioning methods infoMethods for storing different data on different nodesShardingFile 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 factorSource-replica 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 ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Foreign keys infoReferential integritynonoyesyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of command blocks and scriptstunable from ACID to Eventually ConsistentACID
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyes
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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPassword-based authenticationFine grained access rights according to SQL-standard with additional protections for filesUsers, roles and permissions

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More resources
Apache ImpalaDragonflyFaircom DB infoformerly c-treeACEHugeGraph
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