DBMS > EXASOL vs. eXtremeDB vs. HBase vs. Snowflake vs. TerarkDB

System Properties Comparison EXASOL vs. eXtremeDB vs. HBase vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Relational DBMS

Relational DBMS
Time Series DBMS

Wide column store

Relational DBMS

Key-value store

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

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	0.73
Rank	#227	Overall
	#104	Relational DBMS
	#18	Time Series DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

github.com/bytedance/terarkdb

Technical documentation

www.exasol.com/resources

www.mcobject.com/docs/extremedb.htm

hbase.apache.org/book.html

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Exasol

McObject

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2000

2001

2008

2014

2016

Current release

8.2, 2021

2.3.4, January 2021

License

Commercial or Open Source

commercial

Open Source

Apache version 2

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 and C++

Java

C++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
Unix
Windows

using Cygwin

hosted

Data scheme

yes

schema-free, schema definition possible

yes

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

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

support of XML interfaces available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

Java
Lua
Python
R

.Net
C
C#
C++
Java
Lua
Python
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions

yes

Coprocessors in Java

user defined functions

Triggers

yes

by defining events

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning / sharding

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.