DBMS > Axibase vs. GBase vs. Ignite vs. Pinecone vs. Tkrzw

System Properties Comparison Axibase vs. GBase vs. Ignite vs. Pinecone vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A managed, cloud-native vector database

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Vector DBMS

Key-value store

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

axibase.com/docs/atsd/finance

Technical documentation

apacheignite.readme.io/docs

docs.pinecone.io/docs/overview

Developer

Axibase Corporation

General Data Technology Co., Ltd.

Apache Software Foundation

Pinecone Systems, Inc

Mikio Hirabayashi

Initial release

2013

2004

2015

2019

2020

Current release

15585

GBase 8a, GBase 8s, GBase 8c

Apache Ignite 2.6

0.9.3, August 2020

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

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, Java, Python

C++, Java, .Net

C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

hosted

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

String, Number, Boolean

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

SQL-like query language

Standard with numerous extensions

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

RESTful HTTP API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

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

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

using specific database classes

User concepts

Access control

yes

Security Hooks for custom implementations

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

The Ultimate ATV Test: Suzuki's King Quad 750 AXI Rugged Package vs. Alaska's Hunting Season
20 April 2021, Outdoor Life

provided by Google News

Apache Ignite: An Overview
6 September 2023, Open Source For You

GridGain Releases Conference Schedule for Virtual Apache Ignite Summit 2023
1 June 2023, Datanami

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

Fire up big data processing with Apache Ignite
27 October 2016, InfoWorld

provided by Google News

Pinecone’s new serverless database may see few takers, analysts say
17 January 2024, InfoWorld

Pinecone Unveils Serverless Vector Database for Enhanced AI Applications
16 January 2024, Datanami

Reimagining Vector Databases for the Generative AI Era with Pinecone Serverless on AWS | Amazon Web Services
21 March 2024, AWS Blog

Seven Vector Database Startups Poised to Win in the AI Revolution
19 April 2024, Business Insider

Pinecone Brings Serverless To Vector Databases
16 January 2024, Forbes

provided by Google News

Share this page