DBMS > eXtremeDB vs. Riak KV vs. STSdb vs. Vertica vs. Vitess

System Properties Comparison eXtremeDB vs. Riak KV vs. STSdb vs. Vertica vs. Vitess

Editorial information provided by DB-Engines

Name

Description

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

Distributed, fault tolerant key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Key-value store

Relational DBMS

Column oriented

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.mcobject.com

github.com/STSSoft/STSdb4

www.vertica.com

vitess.io

Technical documentation

www.mcobject.com/docs/extremedb.htm

www.tiot.jp/riak-docs/riak/kv/latest

vertica.com/documentation

vitess.io/docs

Developer

McObject

OpenSource, formerly Basho Technologies

STS Soft SC

OpenText

previously Micro Focus and Hewlett Packard

The Linux Foundation, PlanetScale

Initial release

2001

2009

2011

2005

2013

Current release

8.2, 2021

3.2.0, December 2022

4.0.8, September 2015

12.0.3, January 2023

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPLv2, commercial license available

commercial

Limited community edition free

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

Erlang

C++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
OS X

Windows

Linux

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

Secondary indexes

yes

restricted

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

yes

with proprietary extensions

APIs and other access methods

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

HTTP API
Native Erlang Interface

.NET Client API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
Java

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Erlang

yes, PostgreSQL PL/pgSQL, with minor differences

yes

proprietary syntax

Triggers

yes

by defining events

yes

pre-commit hooks and post-commit hooks

yes, called Custom Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

no "single point of failure"

none

horizontal partitioning, hierarchical partitioning

Sharding

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

selectable replication factor

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

table locks or row locks depending on storage engine

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

yes, using Riak Security

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

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

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

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

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» 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

Cost-based models and subscription-based models are both available. One license is...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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