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DBMS > Apache Impala vs. Apache Kylin vs. Badger vs. EJDB vs. Faircom DB

System Properties Comparison Apache Impala vs. Apache Kylin vs. Badger vs. EJDB vs. Faircom DB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Kylin  Xexclude from comparisonBadger  Xexclude from comparisonEJDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Embeddable document-store database library with JSON representation of queries (in MongoDB style)Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.
Primary database modelRelational DBMSRelational DBMSKey-value storeDocument storeKey-value store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.27
Rank#297  Overall
#44  Document stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Websiteimpala.apache.orgkylin.apache.orggithub.com/­dgraph-io/­badgergithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-db
Technical documentationimpala.apache.org/­impala-docs.htmlkylin.apache.org/­docsgodoc.org/­github.com/­dgraph-io/­badgergithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation, originally contributed from eBay IncDGraph LabsSoftmotionsFairCom Corporation
Initial release20132015201720121979
Current release4.1.0, June 20223.1.0, July 2020V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPLv2commercial infoRestricted, free version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaGoCANSI C, C++
Server operating systemsLinuxLinuxBSD
Linux
OS X
Solaris
Windows
server-lessAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Data schemeyesyesschema-freeschema-freeschema free, schema optional, schema required, partial schema,
Typing infopredefined data types such as float or dateyesyesnoyes infostring, integer, double, bool, date, object_idyes, ANSI SQL Types, JSON, typed binary structures
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 indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)nonoyes, ANSI SQL with proprietary extensions
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
in-process shared libraryADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Supported programming languagesAll languages supporting JDBC/ODBCGoActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes info.Net, JavaScript, C/C++
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenoneyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencynoneEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integritynonono infotypically not needed, however similar functionality with collection joins possibleyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononotunable from ACID to Eventually Consistent
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoRead/Write Lockingyes
Durability infoSupport for making data persistentyesyesyesyesYes, tunable from durable to delayed durability to in-memory
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnonoFine grained access rights according to SQL-standard with additional protections for files

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More resources
Apache ImpalaApache KylinBadgerEJDBFaircom DB infoformerly c-treeACE
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