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DBMS > BigchainDB vs. Google Cloud Datastore vs. Hypertable vs. Sphinx vs. Sqrrl

System Properties Comparison BigchainDB vs. Google Cloud Datastore vs. Hypertable vs. Sphinx vs. Sqrrl

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonSphinx  Xexclude from comparisonSqrrl  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as HadoopOpen source search engine for searching in data from different sources, e.g. relational databasesAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument storeDocument storeWide column storeSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.bigchaindb.comcloud.google.com/­datastoresphinxsearch.comsqrrl.com
Technical documentationbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­datastore/­docssphinxsearch.com/­docs
DeveloperGoogleHypertable Inc.Sphinx Technologies Inc.Amazon infooriginally Sqrrl Data, Inc.
Initial release20162008200920012012
Current release0.9.8.11, March 20163.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC++C++Java
Server operating systemsLinuxhostedLinux
OS X
Windows infoan inofficial Windows port is available
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyes, details herenonoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyesrestricted infoonly exact value or prefix value scansyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like query language (SphinxQL)no
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
Proprietary protocolAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresusing Google App Enginenonono
TriggersCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosselectable replication factor on file system levelnoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong 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.Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
BigchainDBGoogle Cloud DatastoreHypertableSphinxSqrrl
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