DBMS > Apache Impala vs. BigObject vs. Ingres vs. SiriDB vs. TerarkDB

System Properties Comparison Apache Impala vs. BigObject vs. Ingres vs. SiriDB vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Analytic DBMS for real-time computations and queries

Well established RDBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

Key-value store

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

impala.apache.org

bigobject.io

www.actian.com/databases/ingres

siridb.com

github.com/bytedance/terarkdb

Technical documentation

impala.apache.org/impala-docs.html

docs.bigobject.io

docs.actian.com/ingres

docs.siridb.com

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

BigObject, Inc.

Actian Corporation

Cesbit

ByteDance, originally Terark

Initial release

2013

2015

1974

originally developed at University Berkely in early 1970s

2017

2016

Current release

4.1.0, June 2022

11.2, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free community edition available

commercial

Open Source

MIT License

commercial

restricted open source version available

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

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

HTTP API

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

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

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Ingres Replicator

yes

none

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

MVCC

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

fine grained access rights according to SQL-standard

simple rights management via user accounts

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More resources

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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28 November 2017, Datanami

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Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

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Actian Launches Ingres as a Fully-Managed Cloud Service
24 September 2021, Integration Developers

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