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DBMS > BigchainDB vs. IRONdb vs. openGauss vs. Sadas Engine vs. Spark SQL

System Properties Comparison BigchainDB vs. IRONdb vs. openGauss vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonIRONdb  Xexclude from comparisonopenGauss  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by HuaweiSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score1.06
Rank#184  Overall
#84  Relational DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.bigchaindb.comwww.circonus.com/solutions/time-series-database/gitee.com/­opengauss
opengauss.org
www.sadasengine.comspark.apache.org/­sql
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.circonus.com/irondb/category/getting-starteddocs.opengauss.org/­en
gitee.com/­opengauss/­docs
www.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCirconus LLC.Huawei and openGauss communitySADAS s.r.l.Apache Software Foundation
Initial release20162017201920062014
Current releaseV0.10.20, January 20183.0, March 20228.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialOpen Sourcecommercial infofree trial version availableOpen Source infoApache 2.0
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 languagePythonC and C++C, C++, JavaC++Scala
Server operating systemsLinuxLinuxLinuxAIX
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyes infotext, numeric, histogramsyesyesyes
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.nonononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)ANSI SQL 2011yesSQL-like DML and DDL statements
APIs and other access methodsCLI Client
RESTful HTTP API
HTTP APIJDBC
ODBC
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C++
Java
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes, in Luayesnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodehorizontal partitioning (by range, list and hash)horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awareSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlyesnoAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles according to SQL-standardno

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More resources
BigchainDBIRONdbopenGaussSadas EngineSpark SQL
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