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

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

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonDatabend  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityWell 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 DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
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
Websitebigobject.iogithub.com/­datafuselabs/­databend
www.databend.com
www.actian.com/­databases/­ingresazure.microsoft.com/­services/­synapse-analyticssplicemachine.com
Technical documentationdocs.bigobject.iodocs.databend.comdocs.actian.com/­ingresdocs.microsoft.com/­azure/­synapse-analyticssplicemachine.com/­how-it-works
DeveloperBigObject, Inc.Databend LabsActian CorporationMicrosoftSplice Machine
Initial release201520211974 infooriginally developed at University Berkely in early 1970s20162014
Current release1.0.59, April 202311.2, May 20223.1, March 2021
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache Version 2.0commercialcommercialOpen 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 languageRustCC++Java
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hosted
Linux
macOS
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
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.nonono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesyesyes
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
CLI Client
JDBC
RESTful HTTP API
.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
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresLuanoyesTransact SQLyes infoJava
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, horizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneIngres ReplicatoryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnoyesno 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 datanoyesACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes 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.yesnoyes
User concepts infoAccess controlnoUsers with fine-grained authorization concept, user rolesfine grained access rights according to SQL-standardyesAccess rights for users, groups and roles according to SQL-standard

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More resources
BigObjectDatabendIngresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSplice Machine
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