DBMS > Cachelot.io vs. Splice Machine vs. WakandaDB vs. XTDB

System Properties Comparison Cachelot.io vs. Splice Machine vs. WakandaDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

cachelot.io

splicemachine.com

wakanda.github.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

splicemachine.com/how-it-works

wakanda.github.io/doc

www.xtdb.com/docs

Developer

Splice Machine

Wakanda SAS

Juxt Ltd.

Initial release

2015

2014

2012

2019

Current release

3.1, March 2021

2.7.0 (April 29, 2019), April 2019

1.19, September 2021

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

AGPL 3.0, commercial license available

Open Source

AGPLv3, extended commercial license available

Open Source

MIT License

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++

Java

C++, JavaScript

Clojure

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Memcached protocol

JDBC
Native Spark Datasource
ODBC

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

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

JavaScript

Clojure
Java

Server-side scripts

Stored procedures

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

yes

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