DBMS > Bangdb vs. InterSystems Caché vs. Microsoft SQL Server vs. Splice Machine

System Properties Comparison Bangdb vs. InterSystems Caché vs. Microsoft SQL Server vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Converged and high performance database for device data, events, time series, document and graph

A multi-model DBMS and application server

Microsofts flagship relational DBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store

Document store
Graph DBMS
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

bangdb.com

www.intersystems.com/products/cache

www.microsoft.com/en-us/sql-server

splicemachine.com

Technical documentation

docs.bangdb.com

docs.intersystems.com

learn.microsoft.com/en-US/sql/sql-server

splicemachine.com/how-it-works

Developer

Sachin Sinha, BangDB

InterSystems

Microsoft

Splice Machine

Initial release

2012

1997

1989

2014

Current release

BangDB 2.0, October 2021

2018.1.4, May 2020

SQL Server 2022, November 2022

3.1, March 2021

License

Commercial or Open Source

Open Source

BSD 3

commercial

restricted free version is available

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

C, C++

C++

Java

Server operating systems

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

depending on used data model

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
C#
C++
Java
Python

C#
C++
Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Java

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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