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DBMS > Apache Impala vs. Datomic vs. etcd vs. Faircom DB

System Properties Comparison Apache Impala vs. Datomic vs. etcd vs. Faircom DB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonetcd  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed reliable key-value storeNative 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 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Websiteimpala.apache.orgwww.datomic.cometcd.io
github.com/­etcd-io/­etcd
www.faircom.com/­products/­faircom-db
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectFairCom Corporation
Initial release201320121979
Current release4.1.0, June 20221.0.6735, June 20233.4, August 2019V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freeOpen Source infoApache Version 2.0commercial infoRestricted, free version available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureGoANSI C, C++
Server operating systemsLinuxAll OS with a Java VMFreeBSD
Linux
Windows infoexperimental
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Data schemeyesyesschema-freeschema free, schema optional, schema required, partial schema,
Typing infopredefined data types such as float or dateyesyesnoyes, 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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes, ANSI SQL with proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIgRPC
JSON over HTTP
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.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-reduceyes infoTransaction Functionsnoyes info.Net, JavaScript, C/C++
TriggersnoBy using transaction functionsyes, watching key changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes, 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 MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnotunable from ACID to Eventually Consistent
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesYes, 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.noyes inforecommended only for testing and developmentnoyes
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 ImpalaDatomicetcdFaircom DB infoformerly c-treeACE
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