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

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

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonBadger  Xexclude from comparisonDatabend  Xexclude from comparisonEJDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparison
DescriptionA 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.An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityEmbeddable 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 DBMSKey-value storeRelational DBMSDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Websitekylin.apache.orggithub.com/­dgraph-io/­badgergithub.com/­datafuselabs/­databend
www.databend.com
github.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-db
Technical documentationkylin.apache.org/­docsgodoc.org/­github.com/­dgraph-io/­badgerdocs.databend.comgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperApache Software Foundation, originally contributed from eBay IncDGraph LabsDatabend LabsSoftmotionsFairCom Corporation
Initial release20152017202120121979
Current release3.1.0, July 20201.0.59, April 2023V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoRustCANSI C, C++
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
hosted
Linux
macOS
server-lessAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Data schemeyesschema-freeyesschema-freeschema free, schema optional, schema required, partial schema,
Typing infopredefined data types such as float or dateyesnoyesyes 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 indexesyesnononoyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)noyesnoyes, ANSI SQL with proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
CLI Client
JDBC
RESTful HTTP API
in-process shared libraryADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Supported programming languagesGoGo
Java
JavaScript (Node.js)
Python
Rust
Actionscript
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 proceduresnononoyes info.Net, JavaScript, C/C++
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnonenonenoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenoneyes, 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 methodsyesnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyEventual 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 datanoyesnotunable 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.nonoyes
User concepts infoAccess controlnoUsers with fine-grained authorization concept, user rolesnoFine grained access rights according to SQL-standard with additional protections for files

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More resources
Apache KylinBadgerDatabendEJDBFaircom DB infoformerly c-treeACE
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