DBMS > atoti vs. etcd vs. Newts vs. Spark SQL vs. TempoIQ

System Properties Comparison atoti vs. etcd vs. Newts vs. Spark SQL vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A distributed reliable key-value store

Time Series DBMS based on Cassandra

Spark SQL is a component on top of 'Spark Core' for structured data processing

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

atoti.io

etcd.io
github.com/etcd-io/etcd

opennms.github.io/newts

spark.apache.org/sql

tempoiq.com (offline)

Technical documentation

docs.atoti.io

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

github.com/OpenNMS/newts/wiki

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

ActiveViam

OpenNMS Group

Apache Software Foundation

TempoIQ

Initial release

2014

2012

Current release

3.4, August 2019

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Scala

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux
OS X
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

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like DML and DDL statements

APIs and other access methods

gRPC
JSON over HTTP

HTTP REST
Java API

JDBC
ODBC

HTTP API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Java

Java
Python
R
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

Python

Triggers

yes, watching key changes

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

based on Cassandra

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

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

simple authentication-based access control

More information provided by the system vendor

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