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DBMS > Databend vs. FatDB vs. Informix vs. RavenDB vs. Spark SQL

System Properties Comparison Databend vs. FatDB vs. Informix vs. RavenDB vs. Spark SQL

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonFatDB  Xexclude from comparisonInformix  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA .NET NoSQL DBMS that can integrate with and extend SQL Server.A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBDocument storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.ibm.com/­products/­informixravendb.netspark.apache.org/­sql
Technical documentationdocs.databend.cominformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
ravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabend LabsFatCloudIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Hibernating RhinosApache Software Foundation
Initial release20212012198420102014
Current release1.0.59, April 202314.10.FC5, November 20205.4, July 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree developer edition availableOpen Source infoAGPL version 3, commercial license 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 languageRustC#C, C++ and JavaC#Scala
Server operating systemshosted
Linux
macOS
WindowsAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infoSince Version 12.10 support for JSON/BSON datatypesnoyes
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.nono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLyesno infoVia inetgration in SQL ServeryesSQL-like query language (RQL)SQL-like DML and DDL statements
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsyesyesno
Triggersnoyes infovia applicationsyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorMulti-source replication
Source-replica replication
Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesno infoCan implement custom security layer via applicationsUsers with fine-grained authentication, authorization, and auditing controlsAuthorization levels configured per client per databaseno

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DatabendFatDBInformixRavenDBSpark SQL
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