DBMS > Apache Impala vs. Microsoft Azure Table Storage vs. RethinkDB vs. TimesTen vs. XTDB

System Properties Comparison Apache Impala vs. Microsoft Azure Table Storage vs. RethinkDB vs. TimesTen vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A Wide Column Store for rapid development using massive semi-structured datasets

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

In-Memory RDBMS compatible to Oracle

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

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	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

impala.apache.org

azure.microsoft.com/en-us/services/storage/tables

rethinkdb.com

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

impala.apache.org/impala-docs.html

rethinkdb.com/docs

docs.oracle.com/database/timesten-18.1

www.xtdb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

The Linux Foundation

since July 2017

Oracle, TimesTen Performance Software, HP

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

Juxt Ltd.

Initial release

2013

2012

2009

1998

2019

Current release

4.1.0, June 2022

2.4.1, August 2020

11 Release 2 (11.2.2.8.0)

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache Version 2

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Clojure

Server operating systems

Linux

hosted

Linux
OS X
Windows

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

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

yes, extensible-data-notation format

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

C
C++
Java
PL/SQL

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL

Triggers

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

Multi-source replication
Source-replica replication

yes, each node contains all data

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

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

optimistic locking

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 rights based on private key authentication or shared access signatures

yes

users and table-level permissions

fine grained access rights according to SQL-standard

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More resources

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