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DBMS > BigchainDB vs. CockroachDB vs. Hazelcast vs. Ignite vs. Sphinx

System Properties Comparison BigchainDB vs. CockroachDB vs. Hazelcast vs. Ignite vs. Sphinx

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonCockroachDB  Xexclude from comparisonHazelcast  Xexclude from comparisonIgnite  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.A widely adopted in-memory data gridApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSKey-value storeKey-value store
Relational DBMS
Search engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.bigchaindb.comwww.cockroachlabs.comhazelcast.comignite.apache.orgsphinxsearch.com
Technical documentationbigchaindb.readthedocs.io/­en/­latestwww.cockroachlabs.com/­docshazelcast.org/­imdg/­docsapacheignite.readme.io/­docssphinxsearch.com/­docs
DeveloperCockroach LabsHazelcastApache Software FoundationSphinx Technologies Inc.
Initial release20162015200820152001
Current release24.1.0, May 20245.3.6, November 2023Apache Ignite 2.63.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL v3Open Source infoApache 2.0, commercial license availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonGoJavaC++, Java, .NetC++
Server operating systemsLinuxLinux
macOS
Windows
All OS with a Java VMLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freedynamic schemaschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyesno
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.nonoyes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes, wire compatible with PostgreSQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)
APIs and other access methodsCLI Client
RESTful HTTP API
JDBCJCache
JPA
Memcached protocol
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes infoEventsyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using RAFTyes infoReplicated Mapyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlyesRole-based access controlRole-based access controlSecurity Hooks for custom implementationsno

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BigchainDBCockroachDBHazelcastIgniteSphinx
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