DBMS > Ehcache vs. Prometheus vs. Snowflake vs. SWC-DB vs. TerarkDB

System Properties Comparison Ehcache vs. Prometheus vs. Snowflake vs. SWC-DB vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Open-source Time Series DBMS and monitoring system

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

A high performance, scalable Wide Column DBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Time Series DBMS

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

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

www.ehcache.org

prometheus.io

www.snowflake.com

github.com/kashirin-alex/swc-db
www.swcdb.org

github.com/bytedance/terarkdb

Technical documentation

www.ehcache.org/documentation

prometheus.io/docs

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Terracotta Inc, owned by Software AG

Snowflake Computing Inc.

Alex Kashirin

ByteDance, originally Terark

Initial release

2009

2015

2014

2020

2016

Current release

3.10.0, March 2022

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

commercial

Open Source

GPL V3

commercial

restricted open source version available

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

Java

C++

Server operating systems

All OS with a Java VM

Linux
Windows

hosted

Linux

Data scheme

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

yes

Secondary indexes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JCache

RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

C++ API
Java API

Supported programming languages

Java

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

JavaScript (Node.js)
Python

C++

C++
Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Cache Event Listeners

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

by Federation

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

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

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