DBMS > Apache Pinot vs. LeanXcale vs. Riak TS vs. TerminusDB

System Properties Comparison Apache Pinot vs. LeanXcale vs. Riak TS vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

pinot.apache.org

www.leanxcale.com

terminusdb.com

Technical documentation

docs.pinot.apache.org

www.tiot.jp/riak-docs/riak/ts/latest

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation and contributors

LeanXcale

Open Source, formerly Basho Technologies

DataChemist Ltd.

Initial release

2015

2018

Current release

1.0.0, September 2023

3.0.0, September 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

Java

Erlang

Prolog, Rust

Server operating systems

All OS with a Java JDK11 or higher

Linux
OS X

Linux

Data scheme

yes

schema-free

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

restricted

SQL

Support of SQL

SQL-like query language

yes

through Apache Derby

yes, limited

SQL-like query language (WOQL)

APIs and other access methods

JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP API
Native Erlang Interface

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Go
Java
Python

C
Java
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript
Python

Server-side scripts

Stored procedures

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

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 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

Role-based access control

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