DBMS > Apache Druid vs. Apache Impala vs. GBase vs. KeyDB

System Properties Comparison Apache Druid vs. Apache Impala vs. GBase vs. KeyDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Analytic DBMS for Hadoop

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Website

druid.apache.org

impala.apache.org

www.gbase.cn

github.com/Snapchat/KeyDB
keydb.dev

Technical documentation

druid.apache.org/docs/latest/design

impala.apache.org/impala-docs.html

docs.keydb.dev

Developer

Apache Software Foundation and contributors

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

General Data Technology Co., Ltd.

EQ Alpha Technology Ltd.

Initial release

2012

2013

2004

2019

Current release

29.0.1, April 2024

4.1.0, June 2022

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2

commercial

Open Source

BSD-3

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

Java

C++

C, Java, Python

C++

Server operating systems

Linux
OS X
Unix

Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

SQL

Support of SQL

SQL for querying

SQL-like DML and DDL statements

Standard with numerous extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages supporting JDBC/ODBC

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

yes

Multi-source replication
Source-replica replication

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

simple password-based access control and ACL

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

Recent citations in the news

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards
26 January 2024, Datanami

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Imply Data gives Apache Druid schema auto-discover capability
6 June 2023, SiliconANGLE News

Imply Announces Automatic Schema Discovery for Apache Druid, Reinforcing Druid's Leadership for Real-Time ...
6 June 2023, businesswire.com

provided by Google News

Cloudera creates observability tool to help enterprises manage cloud costs
6 June 2023, SiliconANGLE News

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Snap snaps up database developer KeyDB to make its infrastructure more snappy
12 May 2022, TechCrunch

Snap Acquires KeyDB for Open-Source Services
17 May 2022, XR Today

Garnet–open-source faster cache-store speeds up applications, services
18 March 2024, microsoft.com

Dragonfly 1.0 Released For What Claims To Be The World's Fastest In-Memory Data Store
20 March 2023, Phoronix

Redis 6 arrives with multithreading for faster I/O
30 April 2020, InfoWorld

provided by Google News

Share this page