DBMS > Apache Impala vs. Axibase vs. EsgynDB vs. Tkrzw

System Properties Comparison Apache Impala vs. Axibase vs. EsgynDB vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

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

Website

impala.apache.org

axibase.com/docs/atsd/finance

www.esgyn.cn

dbmx.net/tkrzw

Technical documentation

impala.apache.org/impala-docs.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Axibase Corporation

Esgyn

Mikio Hirabayashi

Initial release

2013

2015

2020

Current release

4.1.0, June 2022

15585

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

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

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++, Java

C++

Server operating systems

Linux

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

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

All languages supporting JDBC/ODBC/ADO.Net

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

using specific database classes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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