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DBMS > EXASOL vs. Hazelcast vs. Sphinx vs. YugabyteDB

System Properties Comparison EXASOL vs. Hazelcast vs. Sphinx vs. YugabyteDB

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databasesHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSKey-value storeSearch engineRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Score6.03
Rank#60  Overall
#6  Search engines
Score3.11
Rank#99  Overall
#51  Relational DBMS
Websitewww.exasol.comhazelcast.comsphinxsearch.comwww.yugabyte.com
Technical documentationwww.exasol.com/­resourceshazelcast.org/­imdg/­docssphinxsearch.com/­docsdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperExasolHazelcastSphinx Technologies Inc.Yugabyte Inc.
Initial release2000200820012017
Current release5.3.6, November 20233.5.1, February 20232.19, September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageJavaC++C and C++
Server operating systemsAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Data schemeyesschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesSQL-like query languageSQL-like query language (SphinxQL)yes, PostgreSQL compatible
APIs and other access methods.Net
JDBC
ODBC
WebSocket
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocolJDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesJava
Lua
Python
R
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor Servicesnoyes infosql, plpgsql, C
Triggersyesyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapnoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednoDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardRole-based access controlnoyes
More information provided by the system vendor
EXASOLHazelcastSphinxYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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EXASOLHazelcastSphinxYugabyteDB
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