DBMS > EXASOL vs. JaguarDB vs. Memcached vs. Snowflake vs. TerarkDB

System Properties Comparison EXASOL vs. JaguarDB vs. Memcached vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Performant, highly scalable DBMS for AI and IoT applications

In-memory key-value store, originally intended for caching

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

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

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

Score	3.42
Rank	#93	Overall
	#46	Relational DBMS

Score	0.05
Rank	#313	Overall
	#49	Key-value stores

Score	25.97
Rank	#28	Overall
	#4	Key-value stores

Score	15.53
Rank	#37	Overall
	#22	Relational DBMS

Score	0.02
Rank	#323	Overall
	#52	Key-value stores

Website

github.com/Terark/terarkdb

Technical documentation

www.exasol.com/resources

www.datajaguar.com/support.php

github.com/memcached/memcached/wiki

docs.snowflake.net/manuals/index.html

github.com/Terark/terarkdb/wiki

Developer

Exasol

DataJaguar, Inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Snowflake Computing Inc.

Terark

Initial release

2000

2015

2003

2014

2016

Current release

2.9.4 September 2018

1.6.9, November 2020

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

BSD license

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

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Unix
Windows

hosted

Data scheme

yes

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC

Proprietary protocol

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

Java
Lua
Python
R

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Repcached, a Memcached patch, provides this functionallity

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

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 according to SQL-standard

rights management via user accounts

yes

using SASL (Simple Authentication and Security Layer) protocol

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

More information provided by the system vendor

Specific characteristics

SQL support, group by, order by, join
» more

Competitive advantages

Extremely easy to scale-out (in seconds) 100,000 times faster
» more

Typical application scenarios

IoT data, time series data, AI data. Any type of numerical data.
» more

Key customers

Quantea, 2PiDay, Synqy, SinoLogistics, IIVI
» more

Market metrics

Advertising awareness, installed base, brand image, market share
» more

Licensing and pricing models

Free-trial license, per-node license, and subscription license.
» more

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