DBMS > Apache Impala vs. OrientDB vs. Stardog vs. TDSQL for MySQL vs. Teradata

System Properties Comparison Apache Impala vs. OrientDB vs. Stardog vs. TDSQL for MySQL vs. Teradata

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Multi-model DBMS (Document, Graph, Key/Value)

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

impala.apache.org

orientdb.org

www.stardog.com

www.tencentcloud.com/products/dcdb

www.teradata.com

Technical documentation

impala.apache.org/impala-docs.html

www.orientdb.com/docs/last/index.html

docs.stardog.com

www.tencentcloud.com/document/product/1042

docs.teradata.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

OrientDB LTD; CallidusCloud; SAP

Stardog-Union

Tencent

Teradata

Initial release

2013

2010

2013

1984

Current release

4.1.0, June 2022

3.2.29, March 2024

7.3.0, May 2020

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

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++

Java

Server operating systems

Linux

All OS with a Java JDK (>= JDK 6)

Linux
macOS
Windows

hosted

hosted
Linux

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

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.

Import/export of XML data possible

yes

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language, no joins

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C#
C++
Java
PHP
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java, Javascript

user defined functions and aggregates, HTTP Server extensions in Java

yes

UDFs, stored procedures, table functions in parallel

Triggers

Hooks

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic sharding

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

relationships in graphs

yes

Transaction concepts

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

ACID

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users and roles; record level security configurable

Access rights for users and roles

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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