DBMS > Apache Impala vs. Cubrid vs. Splice Machine vs. TerminusDB

System Properties Comparison Apache Impala vs. Cubrid vs. Splice Machine vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Document store

Document store
RDF store

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Website

impala.apache.org

cubrid.com (korean)
cubrid.org (english)

splicemachine.com

terminusdb.com

Technical documentation

impala.apache.org/impala-docs.html

cubrid.org/manuals

splicemachine.com/how-it-works

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CUBRID Corporation, CUBRID Foundation

Splice Machine

DataChemist Ltd.

Initial release

2013

2008

2014

2018

Current release

4.1.0, June 2022

11.0, January 2021

3.1, March 2021

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

AGPL 3.0, commercial license available

Open Source

GPL V3

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++

C, C++, Java

Java

Prolog, Rust

Server operating systems

Linux

Linux
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

JDBC
Native Spark Datasource
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages supporting JDBC/ODBC

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

Access rights for users, groups and roles according to SQL-standard

Role-based access control

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More resources

Recent citations in the news

Cloudera creates observability tool to help enterprises manage cloud costs
6 June 2023, SiliconANGLE News

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

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

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

Splice Machine takes on big boys of big data with Hadoop RDBMS
21 January 2015, RCR Wireless News

provided by Google News

How TerminusDB is commercializing its open source graph database
16 March 2021, VentureBeat

TerminusDB Takes on Data Collaboration with a git-Like Approach
1 December 2020, The New Stack

Dublin-based data collaboration tool TerminusDB raises €3.6 million in seed round
15 March 2021, Tech.eu

Trinity College spinout TerminusDB secures €3.6m in investment
15 March 2021, The Irish Times

[MCR2030-CAMS-ARISE-UNDRR Webinar] Preventing cascading failures of critical assets: Using the Open-Source ...
12 April 2022, United Nations Office for Disaster Risk Reduction

provided by Google News

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