DBMS > Apache Impala vs. BoltDB vs. Kingbase vs. Snowflake

System Properties Comparison Apache Impala vs. BoltDB vs. Kingbase vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An embedded key-value store for Go.

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

impala.apache.org

github.com/boltdb/bolt

www.kingbase.com.cn

www.snowflake.com

Technical documentation

impala.apache.org/impala-docs.html

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

BeiJing KINGBASE Information technologies inc.

Snowflake Computing Inc.

Initial release

2013

1999

2014

Current release

4.1.0, June 2022

V8.0, August 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and Java

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

hosted

Data scheme

yes

schema-free

yes

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

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Standard with numerous extensions

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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.

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

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

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