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DBMS > Databend vs. Hypertable vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Splice Machine

System Properties Comparison Databend vs. Hypertable vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Splice Machine

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonHypertable  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSplice Machine  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines 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 complexityAn open source BigTable implementation based on distributed file systems such as HadoopWell established RDBMSElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSWide column storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.actian.com/­databases/­ingresazure.microsoft.com/­services/­synapse-analyticssplicemachine.com
Technical documentationdocs.databend.comdocs.actian.com/­ingresdocs.microsoft.com/­azure/­synapse-analyticssplicemachine.com/­how-it-works
DeveloperDatabend LabsHypertable Inc.Actian CorporationMicrosoftSplice Machine
Initial release202120091974 infooriginally developed at University Berkely in early 1970s20162014
Current release1.0.59, April 20230.9.8.11, March 201611.2, May 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU version 3. Commercial license availablecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC++CC++Java
Server operating systemshosted
Linux
macOS
Linux
OS X
Windows infoan inofficial Windows port is available
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesnorestricted infoonly exact value or prefix value scansyesyesyes
SQL infoSupport of SQLyesnoyesyesyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
C++ API
Thrift
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
ADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C++
Java
Perl
PHP
Python
Ruby
C#
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesTransact SQLyes infoJava
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, horizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor on file system levelIngres ReplicatoryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes, 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.noyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnofine grained access rights according to SQL-standardyesAccess rights for users, groups and roles according to SQL-standard

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DatabendHypertableIngresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSplice Machine
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