DBMS > Apache Impala vs. HEAVY.AI vs. Kdb vs. RocksDB

System Properties Comparison Apache Impala vs. HEAVY.AI vs. Kdb vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

High performance Time Series DBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Key-value store

Secondary database models

Document store

Spatial DBMS

Relational DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

impala.apache.org

github.com/heavyai/heavydb
www.heavy.ai

kx.com

rocksdb.org

Technical documentation

impala.apache.org/impala-docs.html

docs.heavy.ai

code.kx.com

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

HEAVY.AI, Inc.

Kx Systems, a division of First Derivatives plc

Facebook, Inc.

Initial release

2013

2016

2000

kdb was released 2000, kdb+ in 2003

2013

Current release

4.1.0, June 2022

5.10, January 2022

3.6, May 2018

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2; enterprise edition available

commercial

free 32-bit version

Open Source

BSD

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++

C++ and CUDA

C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

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

table attribute 'grouped'

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language (q)

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Thrift
Vega

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

similar paradigm used for internal processing

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

yes

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

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

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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