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DBMS > etcd vs. Faircom DB vs. Google Cloud Bigtable vs. Ignite

System Properties Comparison etcd vs. Faircom DB vs. Google Cloud Bigtable vs. Ignite

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIgnite  Xexclude from comparison
DescriptionA distributed reliable key-value storeNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelKey-value storeKey-value store
Relational DBMS
Key-value store
Wide column store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.faircom.com/­products/­faircom-dbcloud.google.com/­bigtableignite.apache.org
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­bigtable/­docsapacheignite.readme.io/­docs
DeveloperFairCom CorporationGoogleApache Software Foundation
Initial release197920152015
Current release3.4, August 2019V12, November 2020Apache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoANSI C, C++C++, Java, .Net
Server operating systemsFreeBSD
Linux
Windows infoexperimental
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinux
OS X
Solaris
Windows
Data schemeschema-freeschema free, schema optional, schema required, partial schema,schema-freeyes
Typing infopredefined data types such as float or datenoyes, ANSI SQL Types, JSON, typed binary structuresnoyes
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.nononoyes
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsnoANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsgRPC
JSON over HTTP
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languages.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
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++noyes (compute grid and cache interceptors can be used instead)
Triggersyes, watching key changesyesnoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesUsing 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).Internal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementations

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More resources
etcdFaircom DB infoformerly c-treeACEGoogle Cloud BigtableIgnite
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