DBMS > Apache Impala vs. Microsoft Azure Table Storage vs. SQLite vs. TinkerGraph vs. XTDB

System Properties Comparison Apache Impala vs. Microsoft Azure Table Storage vs. SQLite vs. TinkerGraph 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

Widely used embeddable, in-process RDBMS

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

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

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	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Score	0.12
Rank	#344	Overall
	#34	Graph DBMS

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

impala.apache.org

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

www.sqlite.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

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

Technical documentation

impala.apache.org/impala-docs.html

www.sqlite.org/docs.html

www.xtdb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

Dwayne Richard Hipp

Juxt Ltd.

Initial release

2013

2012

2000

2009

2019

Current release

4.1.0, June 2022

3.45.3 (15 April 2024), April 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Public Domain

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Clojure

Server operating systems

Linux

hosted

server-less

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

Data scheme

yes

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

TinkerPop 3

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Groovy
Java

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

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.

none

yes, each node contains all data

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

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

optional

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

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