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DBMS > Databend vs. Ignite vs. Linter vs. SiteWhere vs. Splice Machine

System Properties Comparison Databend vs. Ignite vs. Linter vs. SiteWhere vs. Splice Machine

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonIgnite  Xexclude from comparisonLinter  Xexclude from comparisonSiteWhere  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.RDBMS for high security requirementsM2M integration platform for persisting/querying time series dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
ignite.apache.orglinter.rugithub.com/­sitewhere/­sitewheresplicemachine.com
Technical documentationdocs.databend.comapacheignite.readme.io/­docssitewhere1.sitewhere.io/­index.htmlsplicemachine.com/­how-it-works
DeveloperDatabend LabsApache Software Foundationrelex.ruSiteWhereSplice Machine
Initial release20212015199020102014
Current release1.0.59, April 2023Apache Ignite 2.63.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen Source infoCommon Public Attribution License Version 1.0Open Source infoAGPL 3.0, commercial license 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 languageRustC++, Java, .NetC and C++JavaJava
Server operating systemshosted
Linux
macOS
Linux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyespredefined schemeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyesnono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLyesnoyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
HTTP RESTJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)yes infoproprietary syntax with the possibility to convert from PL/SQLyes infoJava
Triggersnoyes (cache interceptors and events)yesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding infobased on HBaseShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes (replicated cache)Source-replica replicationselectable replication factor infobased on HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.yesnoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standard

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More resources
DatabendIgniteLinterSiteWhereSplice Machine
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