DBMS > Elasticsearch vs. Google Cloud Spanner vs. Newts vs. RocksDB vs. Valentina Server

System Properties Comparison Elasticsearch vs. Google Cloud Spanner vs. Newts vs. RocksDB vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Time Series DBMS based on Cassandra

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Object-relational database and reports server

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.elastic.co/elasticsearch

cloud.google.com/spanner

opennms.github.io/newts

rocksdb.org

www.valentina-db.net

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

cloud.google.com/spanner/docs

github.com/OpenNMS/newts/wiki

github.com/facebook/rocksdb/wiki

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Elastic

Google

OpenNMS Group

Facebook, Inc.

Paradigma Software

Initial release

2010

2017

2014

2013

1999

Current release

8.6, January 2023

9.2.1, May 2024

5.7.5

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

Apache 2.0

Open Source

BSD

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

C++

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP REST
Java API

C++ API
Java API

ODBC

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Java

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

yes

Concurrency

Support for concurrent manipulation of data

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.

Memcached and Redis integration

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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