DBMS > eXtremeDB vs. Pinecone vs. Postgres-XL vs. WakandaDB

System Properties Comparison eXtremeDB vs. Pinecone vs. Postgres-XL vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

A managed, cloud-native vector database

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS
Time Series DBMS

Vector DBMS

Relational DBMS

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

www.mcobject.com/docs/extremedb.htm

docs.pinecone.io/docs/overview

www.postgres-xl.org/documentation

wakanda.github.io/doc

Developer

McObject

Pinecone Systems, Inc

Wakanda SAS

Initial release

2001

2019

2014

since 2012, originally named StormDB

2012

Current release

8.2, 2021

10 R1, October 2018

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

AGPLv3, extended commercial license 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++

C++, JavaScript

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

distributed, parallel query execution

APIs and other access methods

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

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

Supported programming languages

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

Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

horizontal partitioning

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

fine grained access rights according to SQL-standard

yes

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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