DBMS > etcd vs. EventStoreDB vs. Google BigQuery vs. Sqrrl vs. TinkerGraph

System Properties Comparison etcd vs. EventStoreDB vs. Google BigQuery vs. Sqrrl vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

A distributed reliable key-value store

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Large scale data warehouse service with append-only tables

Adaptable, secure NoSQL built on Apache Accumulo

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Key-value store

Event Store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

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

Score	7.64
Rank	#54	Overall
	#5	Key-value stores

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.12
Rank	#344	Overall
	#34	Graph DBMS

Website

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

www.eventstore.com

cloud.google.com/bigquery

sqrrl.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

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

developers.eventstore.com

cloud.google.com/bigquery/docs

Developer

Event Store Limited

Google

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2010

2012

2009

Current release

3.4, August 2019

21.2, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Open Source

Apache 2.0

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

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux
Windows

hosted

Linux

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

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC
JSON over HTTP

RESTful HTTP/JSON API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

TinkerPop 3

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

making use of Hadoop

none

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

making use of Hadoop

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Since BigQuery is designed for querying data

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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