DBMS > Apache Impala vs. GridDB vs. SiriDB vs. TigerGraph

System Properties Comparison Apache Impala vs. GridDB vs. SiriDB vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Scalable in-memory time series database optimized for IoT and Big Data

Open Source Time Series DBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS

Secondary database models

Document store

Key-value store
Relational DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.griddb.net

docs.siridb.com

docs.tigergraph.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Toshiba Corporation

Cesbit

Initial release

2013

2017

Current release

4.1.0, June 2022

5.1, August 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

MIT License

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++

Server operating systems

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

Numeric data

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

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate consistency within container, eventual consistency across containers

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID at container level

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 can be defined per database

simple rights management via user accounts

Role-based access control

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More resources

Recent citations in the news

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28 November 2017, SDTimes.com

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