DBMS > Apache Impala vs. Axibase vs. HBase vs. TimesTen

System Properties Comparison Apache Impala vs. Axibase vs. HBase vs. TimesTen

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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

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

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.32
Rank	#288	Overall
	#25	Time Series DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Website

impala.apache.org

axibase.com/docs/atsd/finance

hbase.apache.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

impala.apache.org/impala-docs.html

hbase.apache.org/book.html

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Axibase Corporation

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2013

2008

1998

Current release

4.1.0, June 2022

15585

2.3.4, January 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

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

Open Source

Apache version 2

commercial

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

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

options to bring your own types, AVRO

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

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Coprocessors in Java

PL/SQL

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
Source-replica replication

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 or Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

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

fine grained access rights according to SQL-standard

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More resources

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11 August 2021, Krishna Maheshwari (sponsor)

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Recent citations in the 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

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

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9 October 2023, AWS Blog

Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase
20 October 2023, hackernoon.com

Cloudera Search Adds Search Engine Ease to Data on HDFS and Apache HBase
10 December 2023, Channel Futures

HBase: The database big data left behind
6 May 2016, InfoWorld

What Is HBase? (Definition, Uses, Benefits, Features)
22 December 2022, Built In

provided by Google News

In-memory databases with Emulex Gen 7
25 October 2023, Broadcom Inc.

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