DBMS > Datomic vs. Google BigQuery vs. SiriDB vs. Sphinx vs. XTDB

System Properties Comparison Datomic vs. Google BigQuery vs. SiriDB vs. Sphinx vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Large scale data warehouse service with append-only tables

Open Source Time Series DBMS

Open source search engine for searching in data from different sources, e.g. relational databases

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.datomic.com

cloud.google.com/bigquery

siridb.com

sphinxsearch.com

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

Technical documentation

docs.datomic.com

cloud.google.com/bigquery/docs

docs.siridb.com

sphinxsearch.com/docs

www.xtdb.com/docs

Developer

Cognitect

Google

Cesbit

Sphinx Technologies Inc.

Juxt Ltd.

Initial release

2012

2010

2017

2001

2019

Current release

1.0.6735, June 2023

3.5.1, February 2023

1.19, September 2021

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

MIT License

Open Source

GPL version 2, commercial licence available

Open Source

MIT License

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, Clojure

C++

Clojure

Server operating systems

All OS with a Java VM

hosted

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

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

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data

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

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

HTTP API

Proprietary protocol

HTTP REST
JDBC

Supported programming languages

Clojure
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Clojure
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

in JavaScript

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

The original contents of fields are not stored in the Sphinx index.

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

recommended only for testing and development

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

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