DBMS > Apache Impala vs. Badger vs. HBase vs. InfluxDB vs. RocksDB

System Properties Comparison Apache Impala vs. Badger vs. HBase vs. InfluxDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Wide-column store based on Apache Hadoop and on concepts of BigTable

DBMS for storing time series, events and metrics

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

Primary database model

Secondary database models

Document store

Spatial DBMS

with GEO package

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

impala.apache.org

github.com/dgraph-io/badger

hbase.apache.org

www.influxdata.com/products/influxdb-overview

rocksdb.org

Technical documentation

impala.apache.org/impala-docs.html

godoc.org/github.com/dgraph-io/badger

hbase.apache.org/book.html

docs.influxdata.com/influxdb

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DGraph Labs

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Facebook, Inc.

Initial release

2013

2017

2008

2013

Current release

4.1.0, June 2022

2.3.4, January 2021

2.7.6, April 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

MIT-License; commercial enterprise version available

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++

Java

C++

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux
Unix
Windows

using Cygwin

Linux
OS X

through Homebrew

Linux

Data scheme

yes

schema-free

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

Numeric data and Strings

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

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

HTTP API
JSON over UDP

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

in enterprise version only

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication
Source-replica replication

selectable replication factor

in enterprise version only

yes

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

none

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Single row ACID (across millions of columns)

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

Depending on used storage engine

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

News

Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB
6 June 2024

Deadman Alerts with Grafana and InfluxDB Cloud 3.0
5 June 2024

Chasing the Skies: Monitoring Flights with InfluxDB
4 June 2024

Monitoring Your Cloud Environments and Applications with InfluxDB
30 May 2024

Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS
29 May 2024

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.