DBMS > Apache Drill vs. Newts vs. Splice Machine vs. TerarkDB

System Properties Comparison Apache Drill vs. Newts vs. Splice Machine vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Time Series DBMS based on Cassandra

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

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

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Key-value store

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

drill.apache.org

opennms.github.io/newts

splicemachine.com

github.com/bytedance/terarkdb

Technical documentation

drill.apache.org/docs

github.com/OpenNMS/newts/wiki

splicemachine.com/how-it-works

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

OpenNMS Group

Splice Machine

ByteDance, originally Terark

Initial release

2012

2014

2016

Current release

1.20.3, January 2023

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license available

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

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 SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST
Java API

JDBC
Native Spark Datasource
ODBC

C++ API
Java API

Supported programming languages

C++

Java

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

C++
Java

Server-side scripts

Stored procedures

user defined functions

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

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

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