DBMS > Badger vs. Riak TS vs. Splice Machine vs. YDB

System Properties Comparison Badger vs. Riak TS vs. Splice Machine vs. YDB

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

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

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Document store
Relational DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

github.com/dgraph-io/badger

splicemachine.com

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

godoc.org/github.com/dgraph-io/badger

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

splicemachine.com/how-it-works

ydb.tech/en/docs

Developer

DGraph Labs

Open Source, formerly Basho Technologies

Splice Machine

Yandex

Initial release

2017

2015

2014

2019

Current release

3.0.0, September 2022

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license available

Open Source

Apache 2.0; commercial license 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

Erlang

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X

Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, 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

restricted

yes

SQL

Support of SQL

yes, limited

yes

SQL-like query language (YQL)

APIs and other access methods

HTTP API
Native Erlang Interface

JDBC
Native Spark Datasource
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

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

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

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

Erlang

yes

Java

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Multi-source replication
Source-replica replication

Active-passive shard replication

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

Immediate Consistency

Foreign keys

Referential integrity

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

yes, multi-version concurrency control (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 according to SQL-standard

Access rights defined for Yandex Cloud users

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