DBMS > InterSystems Caché vs. LevelDB vs. NSDb vs. Snowflake

System Properties Comparison InterSystems Caché vs. LevelDB vs. NSDb vs. Snowflake

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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

A multi-model DBMS and application server

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.intersystems.com/products/cache

github.com/google/leveldb

nsdb.io

www.snowflake.com

Technical documentation

docs.intersystems.com

github.com/google/leveldb/blob/main/doc/index.md

nsdb.io/Architecture

docs.snowflake.net/manuals/index.html

Developer

InterSystems

Google

Snowflake Computing Inc.

Initial release

1997

2011

2017

2014

Current release

2018.1.4, May 2020

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java, Scala

Server operating systems

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

Illumos
Linux
OS X
Windows

Linux
macOS

hosted

Data scheme

depending on used data model

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

CLI Client
JDBC
ODBC

Supported programming languages

C#
C++
Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Durability

Support for making data persistent

yes

with automatic compression on writes

Using Apache Lucene

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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