DBMS > etcd vs. Google Cloud Datastore vs. OpenSearch vs. SAP IQ vs. TerminusDB

System Properties Comparison etcd vs. Google Cloud Datastore vs. OpenSearch vs. SAP IQ vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Columnar RDBMS optimized for Big Data analytics

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

Primary database model

column-oriented

Secondary database models

Vector DBMS

Document store
RDF store

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

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

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

cloud.google.com/datastore

github.com/opensearch-project
opensearch.org

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

terminusdb.com

Technical documentation

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

cloud.google.com/datastore/docs

opensearch.org/docs/latest

help.sap.com/docs/SAP_IQ

terminusdb.github.io/terminusdb/#

Developer

Google

Amazon Web Services

SAP, formerly Sybase

DataChemist Ltd.

Initial release

2008

2021

1994

2018

Current release

3.4, August 2019

2.5.0, January 2023

16.1 SPS04, April 2019

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

commercial

Open Source

GPL V3

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.

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Implementation language

Java

Prolog, Rust

Server operating systems

FreeBSD
Linux
Windows

experimental

hosted

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

schema-free

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

yes

Typing

predefined data types such as float or date

yes, details here

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 (GQL)

SQL-like query language

yes

SQL-like query language (WOQL)

APIs and other access methods

gRPC
JSON over HTTP

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

using Google App Engine

yes

Triggers

yes, watching key changes

Callbacks using the Google Apps Engine

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication using Paxos

yes

SAP/Sybase Replication Server

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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.

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

Role-based access control

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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